Paper Digest: Recent Papers on Semantic Segmentation
Paper Digest Team extracted all recent Semantic Segmentation related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic.
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TABLE 1: Paper Digest: Recent Papers on Semantic Segmentation
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | Unleashing The Potential of The Diffusion Model in Few-shot Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our initial focus lies in understanding how to facilitate interaction between the query image and the support image, resulting in the proposal of a KV fusion method within the self-attention framework. |
MUZHI ZHU et. al. | arxiv-cs.CV | 2024-10-03 |
| 2 | Deep Multimodal Fusion for Semantic Segmentation of Remote Sensing Earth Observation Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a late fusion deep learning model (LF-DLM) for semantic segmentation that leverages the complementary strengths of both VHR aerial imagery and SITS. |
Ivica Dimitrovski; Vlatko Spasev; Ivan Kitanovski; | arxiv-cs.CV | 2024-10-01 |
| 3 | Semantic Segmentation of Unmanned Aerial Vehicle Remote Sensing Images Using SegFormer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper evaluates the effectiveness and efficiency of SegFormer, a semantic segmentation framework, for the semantic segmentation of UAV images. |
Vlatko Spasev; Ivica Dimitrovski; Ivan Chorbev; Ivan Kitanovski; | arxiv-cs.CV | 2024-10-01 |
| 4 | Weighting Pseudo-Labels Via High-Activation Feature Index Similarity and Object Detection for Semi-Supervised Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel approach to reliably learn from pseudo-labels. |
Prantik Howlader; Hieu Le; Dimitris Samaras; | eccv | 2024-09-30 |
| 5 | I-MedSAM: Implicit Medical Image Segmentation with Segment Anything Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose I-MedSAM, which leverages the benefits of both continuous representations and SAM, to obtain better cross-domain ability and accurate boundary delineation. |
XIAOBAO WEI et. al. | eccv | 2024-09-30 |
| 6 | PSALM: Pixelwise Segmentation with Large Multi-modal Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To overcome the limitation of the LMM being limited to textual output, PSALM incorporates a mask decoder and a well-designed input schema to handle a variety of segmentation tasks. This schema includes images, task instructions, conditional prompts, and mask tokens, which enable the model to generate and classify segmentation masks effectively. |
Zheng Zhang; yeyao ma; Enming Zhang; Xiang Bai; | eccv | 2024-09-30 |
| 7 | Knowledge Transfer with Simulated Inter-Image Erasing for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Though adversarial erasing has prevailed in weakly supervised semantic segmentation to help activate integral object regions, existing approaches still suffer from the dilemma of under-activation and over-expansion due to the difficulty in determining when to stop erasing. In this paper, we propose a Knowledge Transfer with Simulated Inter-Image Erasing (KTSE) approach for weakly supervised semantic segmentation to alleviate the above problem. |
TAO CHEN et. al. | eccv | 2024-09-30 |
| 8 | SegPoint: Segment Any Point Cloud Via Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a model, called , that leverages the reasoning capabilities of a multi-modal Large Language Model (LLM) to produce point-wise segmentation masks across a diverse range of tasks: 1) 3D instruction segmentation, 2) 3D referring segmentation, 3) 3D semantic segmentation, and 4) 3D open-vocabulary semantic segmentation.To advance 3D instruction research, we introduce a new benchmark, , designed to evaluate segmentation performance from complex and implicit instructional texts, featuring point cloud-instruction pairs. |
Shuting He; Henghui Ding; Xudong Jiang; Bihan Wen; | eccv | 2024-09-30 |
| 9 | Beyond Pixels: Semi-Supervised Semantic Segmentation with A Multi-scale Patch-based Multi-Label Classifier Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we show that an effective way to incorporate contextual information is through a patch-based classifier. |
Prantik Howlader; Srijan Das; Hieu Le; Dimitris Samaras; | eccv | 2024-09-30 |
| 10 | Dataset Enhancement with Instance-Level Augmentations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a method for expanding a dataset by incorporating knowledge from the wide distribution of pre-trained latent diffusion models. |
Orest Kupyn; Christian Rupprecht; | eccv | 2024-09-30 |
| 11 | Explore The Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our study delves into the impact of CLIP’s [CLS] token on patch feature correlations, revealing a dominance of ”global” patches that hinders local feature discrimination. To overcome this, we propose CLIPtrase, a novel training-free semantic segmentation strategy that enhances local feature awareness through recalibrated self-correlation among patches. |
Tong Shao; Zhuotao Tian; Hang Zhao; Jingyong Su; | eccv | 2024-09-30 |
| 12 | Open-Vocabulary Camouflaged Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To fill in the gaps, we introduce a new task, open-vocabulary camouflaged object segmentation (OVCOS), and construct a large-scale complex scene dataset (OVCamo) containing 11,483 hand-selected images with fine annotations and corresponding object classes. |
Youwei Pang; Xiaoqi Zhao; JiaMing Zuo; Lihe Zhang; Huchuan Lu; | eccv | 2024-09-30 |
| 13 | SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To adapt the VLM from global to local reasoning, we introduce a spatial fine-tuning strategy for label-efficient learning. |
Lukas Hoyer; David Joseph Tan; Muhammad Ferjad Naeem; Luc Van Gool; Federico Tombari; | eccv | 2024-09-30 |
| 14 | VISA: Reasoning Video Object Segmentation Via Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a new task, Reasoning Video Object Segmentation (ReasonVOS). |
CILIN YAN et. al. | eccv | 2024-09-30 |
| 15 | Enriching Information and Preserving Semantic Congruence in Expanding Curvilinear Object Segmentation Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Curvilinear object segmentation plays a crucial role across various applications, yet datasets in this domain often suffer from small scale due to the high costs associated with data acquisition and annotation. To address these challenges, this paper introduces a novel approach for expanding curvilinear object segmentation datasets, focusing on enhancing the informativeness of generated data and the consistency between semantic maps and generated images. |
Qin Lei; Jiang Zhong; Qizhu Dai; | eccv | 2024-09-30 |
| 16 | Boosting Gaze Object Prediction Via Pixel-level Supervision from Vision Foundation Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a more challenging gaze object segmentation (GOS) task, which involves inferring the pixel-level mask corresponding to the object captured by human gaze behavior. |
Yang Jin; Lei Zhang; Shi Yan; Bin Fan; Binglu Wang; | eccv | 2024-09-30 |
| 17 | MeshSegmenter: Zero-Shot Mesh Segmentation Via Texture Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present MeshSegmenter, a simple yet effective framework designed for zero-shot 3D semantic segmentation. |
ZIMING ZHONG et. al. | eccv | 2024-09-30 |
| 18 | From Pixels to Objects: A Hierarchical Approach for Part and Object Segmentation Using Local and Global Aggregation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a hierarchical transformer-based model designed for sophisticated image segmentation tasks, effectively bridging the granularity of part segmentation with the comprehensive scope of object segmentation. |
Yunfei Xie; Cihang Xie; Alan Yuille; Jieru Mei; | eccv | 2024-09-30 |
| 19 | On The Viability of Monocular Depth Pre-training for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find that monocular depth is a viable form of pre-training for semantic segmentation, validated by improvements over common baselines. Based on the findings, we propose several possible mechanisms behind the improvements, including their relation to dataset size, resolution, architecture, in/out-of-domain source data, and validate them through a wide range of ablation studies. |
DONG LAO et. al. | eccv | 2024-09-30 |
| 20 | View-Consistent Hierarchical 3D Segmentation Using Ultrametric Feature Fields Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we address the challenging task of lifting multi-granular and view-inconsistent image segmentations into a hierarchical and 3D-consistent representation. |
Haodi He; Colton Stearns; Adam Harley; Leonidas Guibas; | eccv | 2024-09-30 |
| 21 | SGS-SLAM: Semantic Gaussian Splatting For Neural Dense SLAM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present SGS-SLAM, the first semantic visual SLAM system based on Gaussian Splatting. |
MINGRUI LI et. al. | eccv | 2024-09-30 |
| 22 | Placing Objects in Context Via Inpainting for Out-of-distribution Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the Placing Objects in Context (POC) pipeline to realistically add any object into any image via diffusion models. |
Pau de Jorge Aranda; Riccardo Volpi; Puneet Dokania; Philip Torr; Gregory Rogez; | eccv | 2024-09-30 |
| 23 | Open Panoramic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To further enhance the distortion-aware modeling ability from the pinhole source domain, we propose a novel data augmentation method called Random Equirectangular Projection (RERP) which is specifically designed to address object deformations in advance. |
JUNWEI ZHENG et. al. | eccv | 2024-09-30 |
| 24 | Segment3D: Learning Fine-Grained Class-Agnostic 3D Segmentation Without Manual Labels Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast, recent 2D foundation models have demonstrated strong generalization and impressive zero-shot abilities, inspiring us to incorporate these characteristics from 2D models into 3D models. Therefore, we explore the use of image segmentation foundation models to automatically generate high-quality training labels for 3D segmentation models. |
RUI HUANG et. al. | eccv | 2024-09-30 |
| 25 | Open-Vocabulary RGB-Thermal Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Second, when fusing RGB and thermal images, they often need to design complex fusion network structures, which usually results in low network training efficiency. We present OpenRSS, the Open-vocabulary RGB-T Semantic Segmentation method, to solve these two disadvantages. |
GUOQIANG ZHAO et. al. | eccv | 2024-09-30 |
| 26 | 3D Weakly Supervised Semantic Segmentation with 2D Vision-Language Guidance Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose 3DSS-VLG, a weakly supervised approach for 3D Semantic Segmentation with 2D Vision-Language Guidance, an alternative approach that a 3D model predicts dense-embedding for each point which is co-embedded with both the aligned image and text spaces from the 2D vision-language model. |
XIAOXU XU et. al. | eccv | 2024-09-30 |
| 27 | ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we carefully re-investigate the architecture of CLIP, and identify residual connections as the primary source of noise that degrades segmentation quality. |
MENGCHENG LAN et. al. | eccv | 2024-09-30 |
| 28 | RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To effectively embed high-dimensional features, we propose a double-nested autoencoder structure with a novel class-aware embedding objective to encode high-dimensional features into manageable voxel-wise embeddings. |
Li Li; Hubert P. H. Shum; Toby P Breckon; | eccv | 2024-09-30 |
| 29 | Class-Agnostic Visio-Temporal Scene Sketch Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Class-Agnostic Visio-Temporal Network (CAVT) for scene sketch semantic segmentation. |
Aleyna Kütük; Tevfik Metin Sezgin; | arxiv-cs.CV | 2024-09-30 |
| 30 | OLAF: A Plug-and-Play Framework for Enhanced Multi-object Multi-part Scene Parsing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the task, we propose a plug-and-play approach termed OLAF. |
Pranav Gupta; Rishubh Singh; Pradeep Shenoy; Ravi Kiran Sarvadevabhatla; | eccv | 2024-09-30 |
| 31 | SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present , a new data generation approach that pushes the performance boundaries of state-of-the-art image segmentation models. |
HANRONG YE et. al. | eccv | 2024-09-30 |
| 32 | MTMamba: Enhancing Multi-Task Dense Scene Understanding By Mamba-Based Decoders Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose MTMamba, a novel Mamba-based architecture for multi-task scene understanding. |
BAIJIONG LIN et. al. | eccv | 2024-09-30 |
| 33 | Occlusion-Aware Seamless Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Panoramic images can broaden the Field of View (FoV), occlusion-aware prediction can deepen the understanding of the scene, and domain adaptation can transfer across viewing domains. In this work, we introduce a novel task, Occlusion-Aware Seamless Segmentation (OASS), which simultaneously tackles all these three challenges. |
YIHONG CAO et. al. | eccv | 2024-09-30 |
| 34 | Towards Reliable Evaluation and Fast Training of Robust Semantic Segmentation Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose several problem-specific novel attacks minimizing different metrics in accuracy and mIoU. |
Francesco Croce; Naman D. Singh; Matthias Hein; | eccv | 2024-09-30 |
| 35 | O2V-Mapping: Online Open-Vocabulary Mapping with Neural Implicit Representation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For the purpose of preserving consistency in 3D object properties across different viewpoints, we propose a spatial adaptive voxel adjustment mechanism and a multi-view weight selection method. |
MUER TIE et. al. | eccv | 2024-09-30 |
| 36 | GTMS: A Gradient-driven Tree-guided Mask-free Referring Image Segmentation Method Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a gradient-driven tree-guided mask-free RIS method, GTMS, which utilizes both structural and semantic information, while only using a bounding box as the supervised signal. |
Haoxin Lv; Tianxiong Zhong; Sanyuan Zhao; | eccv | 2024-09-30 |
| 37 | Can Textual Semantics Mitigate Sounding Object Segmentation Preference? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Motivated by the the fact that text modality is well explored and contains rich abstract semantics, we propose leveraging text cues from the visual scene to enhance audio guidance with the semantics inherent in text. |
Yaoting Wang; Peiwen Sun; Yuanchao Li; Honggang Zhang; Di Hu; | eccv | 2024-09-30 |
| 38 | Betrayed By Attention: A Simple Yet Effective Approach for Self-supervised Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a simple yet effective approach for self-supervised video object segmentation (VOS). |
Shuangrui Ding; Rui Qian; Haohang Xu; Dahua Lin; Hongkai Xiong; | eccv | 2024-09-30 |
| 39 | In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present Lazy Visual Grounding for open-vocabulary semantic segmentation, which decouples unsupervised object mask discovery from object grounding. |
Dahyun Kang; Minsu Cho; | eccv | 2024-09-30 |
| 40 | Segment and Recognize Anything at Any Granularity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce , an augmented image segmentation foundation for segmenting and recognizing anything at desired granularities. |
FENG LI et. al. | eccv | 2024-09-30 |
| 41 | Progressive Proxy Anchor Propagation for Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, relying solely on similarity-based supervision from image-level pretrained models often leads to unreliable guidance due to insufficient patch-level semantic representations. To address this, we propose a Progressive Proxy Anchor Propagation (PPAP) strategy. |
Hyun Seok Seong; WonJun Moon; SuBeen Lee; Jae-Pil Heo; | eccv | 2024-09-30 |
| 42 | One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce VideoLISA, a video-based multimodal large language model designed to tackle the problem of language-instructed reasoning segmentation in videos. |
ZECHEN BAI et. al. | arxiv-cs.CV | 2024-09-29 |
| 43 | Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel method, PixelCLIP, to adapt the CLIP image encoder for pixel-level understanding by guiding the model on where, which is achieved using unlabeled images and masks generated from vision foundation models such as SAM and DINO. |
HEESEONG SHIN et. al. | arxiv-cs.CV | 2024-09-29 |
| 44 | Get It For Free: Radar Segmentation Without Expert Labels and Its Application in Odometry and Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel weakly supervised semantic segmentation method for radar segmentation, where the existing LiDAR semantic segmentation models are employed to generate semantic labels, which then serve as supervision signals for training a radar semantic segmentation model. |
Siru Li; Ziyang Hong; Yushuai Chen; Liang Hu; Jiahu Qin; | arxiv-cs.RO | 2024-09-26 |
| 45 | Global-Local Medical SAM Adaptor Based on Full Adaption Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, Med-SA still can be improved, as it fine-tunes SAM in a partial adaption manner. To resolve this problem, we present a novel global medical SAM adaptor (GMed-SA) with full adaption, which can adapt SAM globally. |
MENG WANG et. al. | arxiv-cs.AI | 2024-09-25 |
| 46 | Go-SLAM: Grounded Object Segmentation and Localization with Gaussian Splatting SLAM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Go-SLAM, a novel framework that utilizes 3D Gaussian Splatting SLAM to reconstruct dynamic environments while embedding object-level information within the scene representations. |
Phu Pham; Dipam Patel; Damon Conover; Aniket Bera; | arxiv-cs.RO | 2024-09-25 |
| 47 | Potential Field As Scene Affordance for Behavior Change-Based Visual Risk Object Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we compute potential fields by assigning different energy levels according to the semantic labels obtained from BEV semantic segmentation. |
Pang-Yuan Pao; Shu-Wei Lu; Ze-Yan Lu; Yi-Ting Chen; | arxiv-cs.CV | 2024-09-24 |
| 48 | The BRAVO Semantic Segmentation Challenge Results in UNCV2024 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose the unified BRAVO challenge to benchmark the reliability of semantic segmentation models under realistic perturbations and unknown out-of-distribution (OOD) scenarios. |
TUAN-HUNG VU et. al. | arxiv-cs.CV | 2024-09-23 |
| 49 | ZeroSCD: Zero-Shot Street Scene Change Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Traditional change detection methods rely on training models that take these image pairs as input and estimate the changes, which requires large amounts of annotated data, a costly and time-consuming process. To overcome this, we propose ZeroSCD, a zero-shot scene change detection framework that eliminates the need for training. |
Shyam Sundar Kannan; Byung-Cheol Min; | arxiv-cs.RO | 2024-09-23 |
| 50 | MOSE: Monocular Semantic Reconstruction Using NeRF-Lifted Noisy Priors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose MOSE, a neural field semantic reconstruction approach to lift inferred image-level noisy priors to 3D, producing accurate semantics and geometry in both 3D and 2D space. |
Zhenhua Du; Binbin Xu; Haoyu Zhang; Kai Huo; Shuaifeng Zhi; | arxiv-cs.CV | 2024-09-21 |
| 51 | CUS3D :CLIP-based Unsupervised 3D Segmentation Via Object-level Denoise Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, unlike previous research that ignores the “noise” raised during feature projection from 2D to 3D, we propose a novel distillation learning framework named CUS3D. |
Fuyang Yu; Runze Tian; Zhen Wang; Xiaochuan Wang; Xiaohui Liang; | arxiv-cs.CV | 2024-09-20 |
| 52 | Enhanced Semantic Segmentation for Large-Scale and Imbalanced Point Clouds Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose the Multilateral Cascading Network (MCNet) for large-scale and sample-imbalanced point cloud scenes. |
Haoran Gong; Haodong Wang; Di Wang; | arxiv-cs.CV | 2024-09-20 |
| 53 | A Bottom-Up Approach to Class-Agnostic Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a novel bottom-up formulation for addressing the class-agnostic segmentation problem. |
Sebastian Dille; Ari Blondal; Sylvain Paris; Yağız Aksoy; | arxiv-cs.CV | 2024-09-20 |
| 54 | HS3-Bench: A Benchmark and Strong Baseline for Hyperspectral Semantic Segmentation in Driving Scenarios Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Even though some datasets exist, there is no standard benchmark available to systematically measure progress on this task and evaluate the benefit of hyperspectral data. In this paper, we work towards closing this gap by providing the HyperSpectral Semantic Segmentation benchmark (HS3-Bench). |
Nick Theisen; Robin Bartsch; Dietrich Paulus; Peer Neubert; | arxiv-cs.CV | 2024-09-17 |
| 55 | Fuse4Seg: Image-Level Fusion Based Multi-Modality Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We argue the current feature-level fusion strategy is prone to semantic inconsistencies and misalignments across various imaging modalities because it merges features at intermediate layers in a neural network without evaluative control. To mitigate this, we introduce a novel image-level fusion based multi-modality medical image segmentation method, Fuse4Seg, which is a bi-level learning framework designed to model the intertwined dependencies between medical image segmentation and medical image fusion. |
Yuchen Guo; Weifeng Su; | arxiv-cs.CV | 2024-09-16 |
| 56 | Semantic2D: A Semantic Dataset for 2D Lidar Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a 2D lidar semantic segmentation dataset to enhance the semantic scene understanding for mobile robots in different indoor robotics applications. |
Zhanteng Xie; Philip Dames; | arxiv-cs.RO | 2024-09-15 |
| 57 | Resolving Inconsistent Semantics in Multi-Dataset Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing methods struggle with this setting, particularly when evaluated on label spaces mixed from the individual training sets. To overcome these issues, we introduce a simple yet effective multi-dataset training approach by integrating language-based embeddings of class names and label space-specific query embeddings. |
Qilong Zhangli; Di Liu; Abhishek Aich; Dimitris Metaxas; Samuel Schulter; | arxiv-cs.CV | 2024-09-15 |
| 58 | Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a method for interpretable semantic segmentation that leverages multi-scale image representation for prototypical part learning. |
Hugo Porta; Emanuele Dalsasso; Diego Marcos; Devis Tuia; | arxiv-cs.CV | 2024-09-14 |
| 59 | ASSNet: Adaptive Semantic Segmentation Network for Microtumors and Multi-Organ Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce an augmented multi-layer perceptron within the encoder to explicitly model long-range dependencies during feature extraction. |
FUCHEN ZHENG et. al. | arxiv-cs.CV | 2024-09-12 |
| 60 | UNIT: Unsupervised Online Instance Segmentation Through Time Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To that end, we leverage an instance segmentation backbone and propose a new training recipe that enables the online tracking of objects. |
Corentin Sautier; Gilles Puy; Alexandre Boulch; Renaud Marlet; Vincent Lepetit; | arxiv-cs.CV | 2024-09-12 |
| 61 | LSVOS Challenge Report: Large-scale Complex and Long Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce the 6th Large-scale Video Object Segmentation (LSVOS) challenge in conjunction with ECCV 2024 workshop. |
HENGHUI DING et. al. | arxiv-cs.CV | 2024-09-09 |
| 62 | Segmentation By Factorization: Unsupervised Semantic Segmentation for Pathology By Factorizing Foundation Model Features Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Segmentation by Factorization (F-SEG), an unsupervised segmentation method for pathology that generates segmentation masks from pre-trained deep learning models. |
Jacob Gildenblat; Ofir Hadar; | arxiv-cs.CV | 2024-09-09 |
| 63 | Enhanced Generative Data Augmentation for Semantic Segmentation Via Stronger Guidance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce an effective data augmentation method for semantic segmentation using the Controllable Diffusion Model. |
Quang-Huy Che; Duc-Tri Le; Vinh-Tiep Nguyen; | arxiv-cs.CV | 2024-09-09 |
| 64 | SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays Via Self-guidance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose a self-guided segmentation framework (SGSeg) that leverages language guidance for training (multi-modal) while enabling text-free inference (uni-modal), which is the first that enables text-free inference in language-guided segmentation. |
Shuchang Ye; Mingyuan Meng; Mingjian Li; Dagan Feng; Jinman Kim; | arxiv-cs.CV | 2024-09-07 |
| 65 | Boundary Feature Fusion Network for Tooth Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces an innovative tooth segmentation network that integrates boundary information to address the issue of indistinct boundaries between teeth and adjacent tissues. |
Dongping Zhang; Zheng Li; Fangao Zeng; Yutong Wei; | arxiv-cs.CV | 2024-09-05 |
| 66 | Evaluation Study on SAM 2 for Class-agnostic Instance-level Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Segment Anything Model (SAM) has demonstrated powerful zero-shot segmentation performance in natural scenes. |
Jialun Pei; Zhangjun Zhou; Tiantian Zhang; | arxiv-cs.CV | 2024-09-04 |
| 67 | AllWeatherNet:Unified Image Enhancement for Autonomous Driving Under Adverse Weather and Lowlight-conditions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing methods have limited effectiveness in improving essential computer vision tasks, such as semantic segmentation, and often focus on only one specific condition, such as removing rain or translating nighttime images into daytime ones. To address these limitations, we propose a method to improve the visual quality and clarity degraded by such adverse conditions. |
CHENGHAO QIAN et. al. | arxiv-cs.CV | 2024-09-03 |
| 68 | Segmenting Object Affordances: Reproducibility and Sensitivity to Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, experimental setups are often not reproducible, thus leading to unfair and inconsistent comparisons. In this work, we benchmark these methods under a reproducible setup on two single objects scenarios, tabletop without occlusions and hand-held containers, to facilitate future comparisons. |
Tommaso Apicella; Alessio Xompero; Paolo Gastaldo; Andrea Cavallaro; | arxiv-cs.CV | 2024-09-03 |
| 69 | LSMS: Language-guided Scale-aware MedSegmentor for Medical Image Referring Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In response, we propose an approach named Language-guided Scale-aware MedSegmentor (LSMS), incorporating two appealing designs: (1)~a Scale-aware Vision-Language Attention module that leverages diverse convolutional kernels to acquire rich visual knowledge and interact closely with linguistic features, thereby enhancing lesion localization capability; (2)~a Full-Scale Decoder that globally models multi-modal features across various scales, capturing complementary information between scales to accurately outline lesion boundaries. |
SHUYI OUYANG et. al. | arxiv-cs.CV | 2024-08-30 |
| 70 | Multi-source Domain Adaptation for Panoramic Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: But, the segmentation model lacks understanding of the panoramic structure when only utilizing real pinhole images, and it lacks perception of real-world scenes when only adopting synthetic panoramic images. Therefore, in this paper, we propose a new task of multi-source domain adaptation for panoramic semantic segmentation, aiming to utilize both real pinhole and synthetic panoramic images in the source domains, enabling the segmentation model to perform well on unlabeled real panoramic images in the target domain. |
JING JIANG et. al. | arxiv-cs.CV | 2024-08-29 |
| 71 | DQFormer: Towards Unified LiDAR Panoptic Segmentation with Decoupled Queries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose decoupling things/stuff queries according to their intrinsic properties for individual decoding and disentangling classification/segmentation to mitigate ambiguity. |
YU YANG et. al. | arxiv-cs.CV | 2024-08-28 |
| 72 | Handling Geometric Domain Shifts in Semantic Segmentation of Surgical RGB and Hyperspectral Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While model development and validation are primarily conducted on idealistic scenes, geometric domain shifts, such as occlusions of the situs, are common in real-world open surgeries. To close this gap, we (1) present the first analysis of state-of-the-art (SOA) semantic segmentation models when faced with geometric out-of-distribution (OOD) data, and (2) propose an augmentation technique called Organ Transplantation, to enhance generalizability. |
SILVIA SEIDLITZ et. al. | arxiv-cs.CV | 2024-08-27 |
| 73 | MROVSeg: Breaking The Resolution Curse of Vision-Language Models in Open-Vocabulary Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although employing additional image backbones for high-resolution inputs can mitigate this issue, it may also introduce significant computation overhead. Therefore, we propose MROVSeg, a multi-resolution training framework for open-vocabulary semantic segmentation with a single pretrained CLIP backbone, that uses sliding windows to slice the high-resolution input into uniform patches, each matching the input size of the well-trained image encoder. |
YUANBING ZHU et. al. | arxiv-cs.CV | 2024-08-27 |
| 74 | ShapeMamba-EM: Fine-Tuning Foundation Model with Local Shape Descriptors and Mamba Blocks for 3D EM Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents ShapeMamba-EM, a specialized fine-tuning method for 3D EM segmentation, which employs adapters for long-range dependency modeling and an encoder for local shape description within the original foundation model. |
RUOHUA SHI et. al. | arxiv-cs.CV | 2024-08-26 |
| 75 | ICFRNet: Image Complexity Prior Guided Feature Refinement for Real-time Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we leverage image complexity as a prior for refining segmentation features to achieve accurate real-time semantic segmentation. |
Xin Zhang; Teodor Boyadzhiev; Jinglei Shi; Jufeng Yang; | arxiv-cs.CV | 2024-08-25 |
| 76 | FusionSAM: Latent Space Driven Segment Anything Model for Multimodal Fusion and Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce SAM into multimodal image segmentation for the first time, proposing a novel framework that combines Latent Space Token Generation (LSTG) and Fusion Mask Prompting (FMP) modules to enhance SAM’s multimodal fusion and segmentation capabilities. |
DAIXUN LI et. al. | arxiv-cs.CV | 2024-08-25 |
| 77 | Accuracy Improvement of Cell Image Segmentation Using Feedback Former Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This tendency leads to a lack of detailed information for segmentation. Therefore, to supplement or reinforce the missing detailed information, we hypothesized that feedback processing in the human visual cortex should be effective. |
Hinako Mitsuoka; Kazuhiro Hotta; | arxiv-cs.CV | 2024-08-23 |
| 78 | Image Segmentation in Foundation Model Era: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We investigate two basic lines of research — generic image segmentation (i.e., semantic segmentation, instance segmentation, panoptic segmentation), and promptable image segmentation (i.e., interactive segmentation, referring segmentation, few-shot segmentation) — by delineating their respective task settings, background concepts, and key challenges. |
TIANFEI ZHOU et. al. | arxiv-cs.CV | 2024-08-23 |
| 79 | Scribbles for All: Benchmarking Scribble Supervised Segmentation Across Datasets Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce Scribbles for All, a label and training data generation algorithm for semantic segmentation trained on scribble labels. |
Wolfgang Boettcher; Lukas Hoyer; Ozan Unal; Jan Eric Lenssen; Bernt Schiele; | arxiv-cs.CV | 2024-08-22 |
| 80 | The 2nd Solution for LSVOS Challenge RVOS Track: Spatial-temporal Refinement for Consistent Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: During testing, while these models can effectively process information over short time steps, they struggle to maintain consistent perception over prolonged time sequences, leading to inconsistencies in the resulting semantic segmentation masks. To address this challenge, we take a step further in this work by leveraging the tracking capabilities of the newly introduced Segment Anything Model version 2 (SAM-v2) to enhance the temporal consistency of the referring object segmentation model. |
Tuyen Tran; | arxiv-cs.CV | 2024-08-22 |
| 81 | Enhancing Cross-Modal Medical Image Segmentation Through Compositionality Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce compositionality as an inductive bias in a cross-modal segmentation network to improve segmentation performance and interpretability while reducing complexity. |
Aniek Eijpe; Valentina Corbetta; Kalina Chupetlovska; Regina Beets-Tan; Wilson Silva; | arxiv-cs.CV | 2024-08-21 |
| 82 | Rethinking Video Segmentation with Masked Video Consistency: Did The Model Learn As Intended? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This leads to inconsistent segmentation results across frames. To address these issues, we propose a training strategy Masked Video Consistency, which enhances spatial and temporal feature aggregation. |
Chen Liang; Qiang Guo; Xiaochao Qu; Luoqi Liu; Ting Liu; | arxiv-cs.CV | 2024-08-20 |
| 83 | Exploring Scene Coherence for Semi-Supervised 3D Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, inter-scene correlation between labeled and unlabeled scenes contribute to transferring rich annotation information, yet this has not been explored for the semi-supervised tasks. To address these two problems, we propose to explore scene coherence for semi-supervised 3D semantic segmentation, dubbed CoScene. |
CHUANDONG LIU et. al. | arxiv-cs.CV | 2024-08-20 |
| 84 | 3D-Aware Instance Segmentation and Tracking in Egocentric Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Egocentric videos present unique challenges for 3D scene understanding due to rapid camera motion, frequent object occlusions, and limited object visibility. This paper introduces a novel approach to instance segmentation and tracking in first-person video that leverages 3D awareness to overcome these obstacles. |
YASH BHALGAT et. al. | arxiv-cs.CV | 2024-08-19 |
| 85 | Segment-Anything Models Achieve Zero-shot Robustness in Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The segment-anything model (SAM) is a generalized image segmentation framework that is capable of handling various types of images and is able to recognize and segment arbitrary objects in an image without the need to train on a specific object. |
JUN YAN et. al. | arxiv-cs.CV | 2024-08-19 |
| 86 | OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce OVOSE, the first Open-Vocabulary Semantic Segmentation algorithm for Event cameras. |
Muhammad Rameez Ur Rahman; Jhony H. Giraldo; Indro Spinelli; Stéphane Lathuilière; Fabio Galasso; | arxiv-cs.CV | 2024-08-18 |
| 87 | Depth-guided Texture Diffusion for Image Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a Depth-guided Texture Diffusion approach that effectively tackles the outlined challenge. |
Wei Sun; Yuan Li; Qixiang Ye; Jianbin Jiao; Yanzhao Zhou; | arxiv-cs.CV | 2024-08-17 |
| 88 | Tuning A SAM-Based Model with Multi-Cognitive Visual Adapter to Remote Sensing Instance Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a Multi-Cognitive SAM-Based Instance Segmentation Model (MC-SAM SEG) is introduced to employ SAM on remote sensing domain. |
Linghao Zheng; Xinyang Pu; Feng Xu; | arxiv-cs.CV | 2024-08-16 |
| 89 | SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a simple but effective framework, termed SAM2-UNet, for versatile image segmentation. |
XINYU XIONG et. al. | arxiv-cs.CV | 2024-08-16 |
| 90 | MetaSeg: MetaFormer-based Global Contexts-aware Network for Efficient Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a powerful semantic segmentation network, MetaSeg, which leverages the Metaformer architecture from the backbone to the decoder. |
Beoungwoo Kang; Seunghun Moon; Yubin Cho; Hyunwoo Yu; Suk-Ju Kang; | arxiv-cs.CV | 2024-08-14 |
| 91 | Enhancing Autonomous Vehicle Perception in Adverse Weather Through Image Augmentation During Semantic Segmentation Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We trained encoder-decoder UNet models to perform semantic segmentation. |
Ethan Kou; Noah Curran; | arxiv-cs.CV | 2024-08-13 |
| 92 | MacFormer: Semantic Segmentation with Fine Object Boundaries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While Vision Transformer-based models have made significant progress, current semantic segmentation methods often struggle with precise predictions in localized areas like object boundaries. To tackle this challenge, we introduce a new semantic segmentation architecture, “MacFormer”, which features two key components. |
GUOAN XU et. al. | arxiv-cs.CV | 2024-08-11 |
| 93 | TOSS: Real-time Tracking and Moving Object Segmentation for Static Scene Mapping Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an integrated real-time framework that combines online tracking-based moving object segmentation with static map building. |
SEOYEON JANG et. al. | arxiv-cs.RO | 2024-08-10 |
| 94 | SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite its advancements, SAM encountered limitations in handling some complex low-level segmentation tasks like camouflaged object and medical imaging. In response, in 2023, we introduced SAM-Adapter, which demonstrated improved performance on these challenging tasks. |
TIANRUN CHEN et. al. | arxiv-cs.CV | 2024-08-08 |
| 95 | Embodied Uncertainty-Aware Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To deal with uncertainty in robot perception, we propose a method for generating a hypothesis distribution of object segmentation. |
Xiaolin Fang; Leslie Pack Kaelbling; Tomás Lozano-Pérez; | arxiv-cs.RO | 2024-08-08 |
| 96 | SegXAL: Explainable Active Learning for Semantic Segmentation in Driving Scene Scenarios Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there are certain challenges that hinder the deployment of AI models in-the-wild scenarios, i.e., inefficient use of unlabeled data, lack of incorporation of human expertise, and lack of interpretation of the results. To mitigate these challenges, we propose a novel Explainable Active Learning (XAL) model, XAL-based semantic segmentation model SegXAL, that can (i) effectively utilize the unlabeled data, (ii) facilitate the Human-in-the-loop paradigm, and (iii) augment the model decisions in an interpretable way. |
Sriram Mandalika; Athira Nambiar; | arxiv-cs.CV | 2024-08-08 |
| 97 | Biomedical SAM 2: Segment Anything in Biomedical Images and Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To explore the performance of SAM-2 in biomedical applications, we designed three evaluation pipelines for single-frame 2D image segmentation, multi-frame 3D image segmentation and multi-frame video segmentation with varied prompt designs, revealing SAM-2’s limitations in medical contexts. |
ZHILING YAN et. al. | arxiv-cs.CV | 2024-08-06 |
| 98 | Segmentation Style Discovery: Application to Skin Lesion Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce the problem of segmentation style discovery, and propose StyleSeg, a segmentation method that learns plausible, diverse, and semantically consistent segmentation styles from a corpus of image-mask pairs without any knowledge of annotator correspondence. |
Kumar Abhishek; Jeremy Kawahara; Ghassan Hamarneh; | arxiv-cs.CV | 2024-08-05 |
| 99 | Pixel-Level Domain Adaptation: A New Perspective for Enhancing Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we argue that the distribution discrepancy between the discriminative and the non-discriminative parts of objects prevents the model from producing complete and precise pseudo masks as ground truths. |
Ye Du; Zehua Fu; Qingjie Liu; | arxiv-cs.CV | 2024-08-04 |
| 100 | A Robotics-Inspired Scanpath Model Reveals The Importance of Uncertainty and Semantic Object Cues for Gaze Guidance in Dynamic Scenes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Still, object segmentation and gaze behavior are typically treated as two independent processes. Drawing on an information processing pattern from robotics, we present a mechanistic model that simulates these processes for dynamic real-world scenes. |
Vito Mengers; Nicolas Roth; Oliver Brock; Klaus Obermayer; Martin Rolfs; | arxiv-cs.CV | 2024-08-02 |
| 101 | Medical SAM 2: Segment Medical Images As Video Via Segment Anything Model 2 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce Medical SAM 2 (MedSAM-2), an advanced segmentation model that utilizes the SAM 2 framework to address both 2D and 3D medical image segmentation tasks. |
Jiayuan Zhu; Yunli Qi; Junde Wu; | arxiv-cs.CV | 2024-08-01 |
| 102 | Point-supervised Brain Tumor Segmentation with Box-prompted MedSAM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although recent vision foundational models, such as the medical segment anything model (MedSAM), have made significant advancements in bounding-box-prompted segmentation, it is not straightforward to utilize point annotation, and is prone to semantic ambiguity. In this preliminary study, we introduce an iterative framework to facilitate semantic-aware point-supervised MedSAM. |
Xiaofeng Liu; Jonghye Woo; Chao Ma; Jinsong Ouyang; Georges El Fakhri; | arxiv-cs.CV | 2024-08-01 |
| 103 | Synthetic Dual Image Generation for Reduction of Labeling Efforts in Semantic Segmentation of Micrographs with A Customized Metric Function Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The latter will eventually be decoded by VQ-VAE to generate images alongside corresponding masks for semantic segmentation. To evaluate the synthetic data, we have trained U-Net models with different amounts of these synthetic data in conjunction with real data. |
Matias Oscar Volman Stern; Dominic Hohs; Andreas Jansche; Timo Bernthaler; Gerhard Schneider; | arxiv-cs.CV | 2024-08-01 |
| 104 | MaskUno: Switch-Split Block For Enhancing Instance Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In all the proposed variations to date, the problem of competing kernels (each class aims to maximize its own accuracy) persists when models try to synchronously learn numerous classes. In this paper, we propose mitigating this problem by replacing mask prediction with a Switch-Split block that processes refined ROIs, classifies them, and assigns them to specialized mask predictors. |
Jawad Haidar; Marc Mouawad; Imad Elhajj; Daniel Asmar; | arxiv-cs.CV | 2024-07-31 |
| 105 | 3D-GRES: Generalized 3D Referring Expression Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, current approaches are limited to segmenting a single target, restricting the versatility of the task. To overcome this limitation, we introduce Generalized 3D Referring Expression Segmentation (3D-GRES), which extends the capability to segment any number of instances based on natural language instructions. |
CHANGLI WU et. al. | arxiv-cs.CV | 2024-07-30 |
| 106 | Leveraging Adaptive Implicit Representation Mapping for Ultra High-Resolution Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Secondly, SIRMF is shared across all samples, which limits its ability to generalize and handle diverse inputs. To address these limitations, we propose a novel approach that leverages the newly proposed Adaptive Implicit Representation Mapping (AIRM) for ultra-high-resolution Image Segmentation. |
Ziyu Zhao; Xiaoguang Li; Pingping Cai; Canyu Zhang; Song Wang; | arxiv-cs.CV | 2024-07-30 |
| 107 | Fine-grained Metrics for Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Because of this, the majority of categories and large objects are favored in the existing evaluation metrics. This paper suggests fine-grained mIoU and mAcc for a more thorough assessment of point cloud segmentation algorithms in order to address these issues. |
Zhuheng Lu; Ting Wu; Yuewei Dai; Weiqing Li; Zhiyong Su; | arxiv-cs.CV | 2024-07-30 |
| 108 | ASI-Seg: Audio-Driven Surgical Instrument Segmentation with Surgeon Intention Understanding Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The recent Segment Anything Model (SAM) reveals the capability to segment objects following prompts, but the manual annotations for prompts are impractical during the surgery. To address these limitations in operating rooms, we propose an audio-driven surgical instrument segmentation framework, named ASI-Seg, to accurately segment the required surgical instruments by parsing the audio commands of surgeons. |
ZHEN CHEN et. al. | arxiv-cs.CV | 2024-07-28 |
| 109 | RefMask3D: Language-Guided Transformer for 3D Referring Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose RefMask3D to explore the comprehensive multi-modal feature interaction and understanding. |
Shuting He; Henghui Ding; | arxiv-cs.CV | 2024-07-25 |
| 110 | SMPISD-MTPNet: Scene Semantic Prior-Assisted Infrared Ship Detection Using Multi-Task Perception Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For the training process, we introduce the Soft Fine-tuning training strategy to suppress the distortion caused by data augmentation. |
CHEN HU et. al. | arxiv-cs.CV | 2024-07-25 |
| 111 | Navigating Uncertainty in Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We address the selection and evaluation of uncertain segmentation methods in medical imaging and present two case studies: prostate segmentation, illustrating that for minimal annotator variation simple deterministic models can suffice, and lung lesion segmentation, highlighting the limitations of the Generalized Energy Distance (GED) in model selection. |
Kilian Zepf; Jes Frellsen; Aasa Feragen; | arxiv-cs.CV | 2024-07-23 |
| 112 | Deformable Convolution Based Road Scene Semantic Segmentation of Fisheye Images in Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates the effectiveness of modern Deformable Convolutional Neural Networks (DCNNs) for semantic segmentation tasks, particularly in autonomous driving scenarios with fisheye images. |
ANAM MANZOOR et. al. | arxiv-cs.CV | 2024-07-23 |
| 113 | Disentangling Spatio-temporal Knowledge for Weakly Supervised Object Detection and Segmentation in Surgical Video Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces Video Spatio-Temporal Disentanglement Networks (VDST-Net), a framework to disentangle spatiotemporal information using semi-decoupled knowledge distillation to predict high-quality class activation maps (CAMs). |
Guiqiu Liao; Matjaz Jogan; Sai Koushik; Eric Eaton; Daniel A. Hashimoto; | arxiv-cs.CV | 2024-07-22 |
| 114 | Augmented Efficiency: Reducing Memory Footprint and Accelerating Inference for 3D Semantic Segmentation Through Hybrid Vision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel approach to 3D semantic segmentation, distinguished by incorporating a hybrid blend of 2D and 3D computer vision techniques, enabling a streamlined, efficient process. |
Aditya Krishnan; Jayneel Vora; Prasant Mohapatra; | arxiv-cs.CV | 2024-07-22 |
| 115 | GaussianBeV: 3D Gaussian Representation Meets Perception Models for BeV Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose GaussianBeV, a novel method for transforming image features to BeV by finely representing the scene using a set of 3D gaussians located and oriented in 3D space. |
Florian Chabot; Nicolas Granger; Guillaume Lapouge; | arxiv-cs.CV | 2024-07-19 |
| 116 | Panoptic Segmentation of Mammograms with Text-To-Image Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We aim to harness their capabilities for breast lesion segmentation in a panoptic setting, which encompasses both semantic and instance-level predictions. |
Kun Zhao; Jakub Prokop; Javier Montalt Tordera; Sadegh Mohammadi; | arxiv-cs.CV | 2024-07-19 |
| 117 | ViLLa: Video Reasoning Segmentation with Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To bridge the gap between image and video, in this work, we propose a new video segmentation task – video reasoning segmentation. |
RONGKUN ZHENG et. al. | arxiv-cs.CV | 2024-07-18 |
| 118 | MeshSegmenter: Zero-Shot Mesh Semantic Segmentation Via Texture Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present MeshSegmenter, a simple yet effective framework designed for zero-shot 3D semantic segmentation. |
ZIMING ZHONG et. al. | arxiv-cs.CV | 2024-07-18 |
| 119 | Denoising Diffusions in Latent Space for Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel conditional generative modeling framework (LDSeg) that performs diffusion in latent space for medical image segmentation. |
FAHIM AHMED ZAMAN et. al. | arxiv-cs.CV | 2024-07-17 |
| 120 | OE-BevSeg: An Object Informed and Environment Aware Multimodal Framework for Bird’s-eye-view Vehicle Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there are still two issues: 1) a lack of effective understanding and enhancement of BEV space features, particularly in accurately capturing long-distance environmental features and 2) recognizing fine details of target objects. To address these issues, we propose OE-BevSeg, an end-to-end multimodal framework that enhances BEV segmentation performance through global environment-aware perception and local target object enhancement. |
JIAN SUN et. al. | arxiv-cs.CV | 2024-07-17 |
| 121 | VISA: Reasoning Video Object Segmentation Via Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a new task, Reasoning Video Object Segmentation (ReasonVOS). |
CILIN YAN et. al. | arxiv-cs.CV | 2024-07-15 |
| 122 | RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To effectively embed high-dimensional RAPiD features, we propose a double-nested autoencoder structure with a novel class-aware embedding objective to encode high-dimensional features into manageable voxel-wise embeddings. |
Li Li; Hubert P. H. Shum; Toby P. Breckon; | arxiv-cs.CV | 2024-07-14 |
| 123 | FANet: Feature Amplification Network for Semantic Segmentation in Cluttered Background Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing deep learning approaches leave out the semantic cues that are crucial in semantic segmentation present in complex scenarios including cluttered backgrounds and translucent objects, etc. To handle these challenges, we propose a feature amplification network (FANet) as a backbone network that incorporates semantic information using a novel feature enhancement module at multi-stages. |
Muhammad Ali; Mamoona Javaid; Mubashir Noman; Mustansar Fiaz; Salman Khan; | arxiv-cs.CV | 2024-07-12 |
| 124 | Enriching Information and Preserving Semantic Consistency in Expanding Curvilinear Object Segmentation Datasets Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Curvilinear object segmentation plays a crucial role across various applications, yet datasets in this domain often suffer from small scale due to the high costs associated with data acquisition and annotation. To address these challenges, this paper introduces a novel approach for expanding curvilinear object segmentation datasets, focusing on enhancing the informativeness of generated data and the consistency between semantic maps and generated images. |
Qin Lei; Jiang Zhong; Qizhu Dai; | arxiv-cs.CV | 2024-07-11 |
| 125 | CycleSAM: One-Shot Surgical Scene Segmentation Using Cycle-Consistent Feature Matching to Prompt SAM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose CycleSAM, an approach for one-shot surgical scene segmentation that uses the training image-mask pair at test-time to automatically identify points in the test images that correspond to each object class, which can then be used to prompt SAM to produce object masks. |
Aditya Murali; Pietro Mascagni; Didier Mutter; Nicolas Padoy; | arxiv-cs.CV | 2024-07-09 |
| 126 | Submodular Video Object Proposal Selection for Semantic Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes to achieve semantic video object segmentation by learning a data-driven representation which captures the synergy of multiple instances from continuous frames. |
Tinghuai Wang; | arxiv-cs.CV | 2024-07-08 |
| 127 | LuSNAR:A Lunar Segmentation, Navigation and Reconstruction Dataset Based on Muti-sensor for Autonomous Exploration Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Most of the existing lunar datasets are targeted at a single task, lacking diverse scenes and high-precision ground truth labels. To address this issue, we propose a multi-task, multi-scene, and multi-label lunar benchmark dataset LuSNAR. |
JIAYI LIU et. al. | arxiv-cs.CV | 2024-07-08 |
| 128 | Object-Oriented Material Classification and 3D Clustering for Improved Semantic Perception and Mapping in Mobile Robots Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a complementarity-aware deep learning approach for RGB-D-based material classification built on top of an object-oriented pipeline. |
Siva Krishna Ravipati; Ehsan Latif; Ramviyas Parasuraman; Suchendra M. Bhandarkar; | arxiv-cs.RO | 2024-07-08 |
| 129 | RHRSegNet: Relighting High-Resolution Night-Time Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose RHRSegNet, implementing a relighting model over a High-Resolution Network for semantic segmentation. |
Sarah Elmahdy; Rodaina Hebishy; Ali Hamdi; | arxiv-cs.CV | 2024-07-08 |
| 130 | Self-supervised Learning Via Cluster Distance Prediction for Operating Room Context Awareness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new 3D self-supervised task for OR scene understanding utilizing OR scene images captured with ToF cameras. |
Idris Hamoud; Alexandros Karargyris; Aidean Sharghi; Omid Mohareri; Nicolas Padoy; | arxiv-cs.CV | 2024-07-07 |
| 131 | LMSeg: A Deep Graph Message-passing Network for Efficient and Accurate Semantic Segmentation of Large-scale 3D Landscape Meshes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents an end-to-end deep graph message-passing network, LMSeg, designed to efficiently and accurately perform semantic segmentation on large-scale 3D landscape meshes. |
Zexian Huang; Kourosh Khoshelham; Gunditj Mirring Traditional Owners Corporation; Martin Tomko; | arxiv-cs.CV | 2024-07-05 |
| 132 | Attention Normalization Impacts Cardinality Generalization in Slot Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we show that design decisions on normalizing the aggregated values in the attention architecture have considerable impact on the capabilities of Slot Attention to generalize to a higher number of slots and objects as seen during training. |
Markus Krimmel; Jan Achterhold; Joerg Stueckler; | arxiv-cs.CV | 2024-07-04 |
| 133 | A Unified Framework for 3D Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose UniSeg3D, a unified 3D segmentation framework that achieves panoptic, semantic, instance, interactive, referring, and open-vocabulary semantic segmentation tasks within a single model. |
WEI XU et. al. | arxiv-cs.CV | 2024-07-03 |
| 134 | ISWSST: Index-space-wave State Superposition Transformers for Multispectral Remotely Sensed Imagery Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Currently the semantic segmentation task of multispectral remotely sensed imagery (MSRSI) faces the following problems: 1) Usually, only single domain feature (i.e., space domain … |
Chang Li; Pengfei Zhang; Yu Wang; | arxiv-cs.CV | 2024-07-03 |
| 135 | HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose to complement discriminative segmentation methods with the knowledge of underlying data distribution from generative models. |
Tao Chen; Chenhui Wang; Zhihao Chen; Yiming Lei; Hongming Shan; | arxiv-cs.CV | 2024-07-03 |
| 136 | Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we aim to learn multi-grained representations, which can effectively describe the image on various granularity levels, thus improving generalization on extensive downstream tasks. |
Chengchao Shen; Jianzhong Chen; Jianxin Wang; | arxiv-cs.CV | 2024-07-02 |
| 137 | MTMamba: Enhancing Multi-Task Dense Scene Understanding By Mamba-Based Decoders Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose MTMamba, a novel Mamba-based architecture for multi-task scene understanding. |
BAIJIONG LIN et. al. | arxiv-cs.CV | 2024-07-02 |
| 138 | Joint Optimization of Crack Segmentation With An Adaptive Dynamic Threshold Module Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Crack segmentation is a critical component in structural health monitoring. Conventional crack segmentation models usually focus on optimizing the cross-entropy-based objective … |
Qin Lei; Jiang Zhong; Chen Wang; | IEEE Transactions on Intelligent Transportation Systems | 2024-07-01 |
| 139 | PanopticRecon: Leverage Open-vocabulary Instance Segmentation for Zero-shot Panoptic Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel zero-shot panoptic reconstruction method from RGB-D images of scenes. |
XUAN YU et. al. | arxiv-cs.CV | 2024-07-01 |
| 140 | Fast and Efficient: Mask Neural Fields for 3D Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents MaskField, which enables fast and efficient 3D open-vocabulary segmentation with neural fields under weak supervision. |
ZIHAN GAO et. al. | arxiv-cs.CV | 2024-07-01 |
| 141 | Mobile Robot Oriented Large-Scale Indoor Dataset for Dynamic Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These experiments reveal serious challenges for some robot scene understanding tasks in dynamic scenes. By sharing this dataset, we aim to foster and iterate new mobile robot algorithms quickly for robot actual working dynamic environment, i.e. complex crowded dynamic scenes. |
YIFAN TANG et. al. | arxiv-cs.RO | 2024-06-28 |
| 142 | Segment Anything Model for Automated Image Data Annotation: Empirical Studies Using Text Prompts from Grounding DINO Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we perform empirical studies on six publicly available datasets across different domains and reveal that these errors consistently follow a predictable pattern and can, thus, be mitigated by a simple strategy. |
Fuseini Mumuni; Alhassan Mumuni; | arxiv-cs.CV | 2024-06-27 |
| 143 | Precision Matters: Precision-aware Ensemble for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In the same vein, we propose ORANDNet, an advanced ensemble approach tailored for WSSS. |
Junsung Park; Hyunjung Shim; | arxiv-cs.CV | 2024-06-27 |
| 144 | PPTFormer: Pseudo Multi-Perspective Transformer for UAV Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Traditional segmentation algorithms falter as they cannot accurately mimic the complexity of UAV perspectives, and the cost of obtaining multi-perspective labeled datasets is prohibitive. To address these issues, we introduce the PPTFormer, a novel \textbf{P}seudo Multi-\textbf{P}erspective \textbf{T}rans\textbf{former} network that revolutionizes UAV image segmentation. |
Deyi Ji; Wenwei Jin; Hongtao Lu; Feng Zhao; | arxiv-cs.CV | 2024-06-27 |
| 145 | SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cues Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a novel framework, SimTxtSeg, that leverages simple text cues to generate high-quality pseudo-labels and study the cross-modal fusion in training segmentation models, simultaneously. |
Yuxin Xie; Tao Zhou; Yi Zhou; Geng Chen; | arxiv-cs.CV | 2024-06-27 |
| 146 | CAS: Confidence Assessments of Classification Algorithms for Semantic Segmentation of EO Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The model we develop, the Confidence Assessments of classification algorithms for Semantic segmentation (CAS) model, performs confidence evaluations at both the segment and pixel levels, and outputs both labels and confidence. |
Nikolaos Dionelis; Nicolas Longepe; | arxiv-cs.CV | 2024-06-26 |
| 147 | Principal Component Clustering for Semantic Segmentation in Synthetic Data Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This technical report outlines our method for generating a synthetic dataset for semantic segmentation using a latent diffusion model. |
Felix Stillger; Frederik Hasecke; Tobias Meisen; | arxiv-cs.CV | 2024-06-25 |
| 148 | LOGCAN++: Adaptive Local-global Class-aware Network for Semantic Segmentation of Remote Sensing Imagery Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose our LOGCAN++, a semantic segmentation model customized for remote sensing images, which is made up of a Global Class Awareness (GCA) module and several Local Class Awareness (LCA) modules. |
XIAOWEN MA et. al. | arxiv-cs.CV | 2024-06-24 |
| 149 | SegNet4D: Effective and Efficient 4D LiDAR Semantic Segmentation in Autonomous Driving Environments Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this article, we introduce SegNet4D, a novel real-time multi-scan semantic segmentation method leveraging a projection-based approach for fast motion feature encoding, showcasing outstanding performance. |
NENG WANG et. al. | arxiv-cs.CV | 2024-06-23 |
| 150 | Fine-grained Background Representation for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a simple fine-grained background representation (FBR) method to discover and represent diverse BG semantics and address the co-occurring problems. |
XU YIN et. al. | arxiv-cs.CV | 2024-06-22 |
| 151 | EvSegSNN: Neuromorphic Semantic Segmentation for Event Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, due to their huge computational costs and their high memory consumption, these models are not meant to be deployed on resource-constrained systems. To address this limitation, we introduce an end-to-end biologically inspired semantic segmentation approach by combining Spiking Neural Networks (SNNs, a low-power alternative to classical neural networks) with event cameras whose output data can directly feed these neural network inputs. |
Dalia Hareb; Jean Martinet; | arxiv-cs.CV | 2024-06-20 |
| 152 | Seg-LSTM: Performance of XLSTM for Semantic Segmentation of Remotely Sensed Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our study found that Vision-LSTM’s performance in semantic segmentation was limited and generally inferior to Vision-Transformers-based and Vision-Mamba-based models in most comparative tests. |
Qinfeng Zhu; Yuanzhi Cai; Lei Fan; | arxiv-cs.CV | 2024-06-20 |
| 153 | Evaluation of Deep Learning Semantic Segmentation for Land Cover Mapping on Multispectral, Hyperspectral and High Spatial Aerial Imagery Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research implemented a semantic segmentation method such as Unet, Linknet, FPN, and PSPnet for categorizing vegetation, water, and others (i.e., soil and impervious surface). |
Ilham Adi Panuntun; Ying-Nong Chen; Ilham Jamaluddin; Thi Linh Chi Tran; | arxiv-cs.CV | 2024-06-20 |
| 154 | Reparameterizable Dual-Resolution Network for Real-time Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Although existing real-time semantic segmentation models achieve a commendable balance between accuracy and speed, their multi-path blocks still affect overall speed. To address this issue, this study proposes a Reparameterizable Dual-Resolution Network (RDRNet) dedicated to real-time semantic segmentation. |
Guoyu Yang; Yuan Wang; Daming Shi; | arxiv-cs.CV | 2024-06-18 |
| 155 | Learning from Exemplars for Interactive Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we introduce novel interactive segmentation frameworks for both a single object and multiple objects in the same category. |
Kun Li; Hao Cheng; George Vosselman; Michael Ying Yang; | arxiv-cs.CV | 2024-06-17 |
| 156 | OoDIS: Anomaly Instance Segmentation Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Development in this area has been lagging, largely due to the lack of dedicated benchmarks. To address this gap, we have extended the most commonly used anomaly segmentation benchmarks to include the instance segmentation task. |
ALEXEY NEKRASOV et. al. | arxiv-cs.CV | 2024-06-17 |
| 157 | Frozen CLIP: A Strong Backbone for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose WeCLIP, a CLIP-based single-stage pipeline, for weakly supervised semantic segmentation. |
Bingfeng Zhang; Siyue Yu; Yunchao Wei; Yao Zhao; Jimin Xiao; | arxiv-cs.CV | 2024-06-16 |
| 158 | PyramidMamba: Rethinking Pyramid Feature Fusion with Selective Space State Model for Semantic Segmentation of Remote Sensing Imagery Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the actual multi-scale feature fusion often comes with the semantic redundancy issue due to homogeneous semantic contents in pyramid features. To handle this issue, we propose a novel Mamba-based segmentation network, namely PyramidMamba. |
LIBO WANG et. al. | arxiv-cs.CV | 2024-06-16 |
| 159 | Open-Vocabulary Semantic Segmentation with Image Embedding Balancing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Although many efforts have been made to utilize powerful CLIP models to accomplish this task, they are still easily overfitting to training classes due to the natural gaps in semantic information between training and new classes. To overcome this challenge, we propose a novel framework for openvocabulary semantic segmentation called EBSeg, incorporating an Adaptively Balanced Decoder (AdaB Decoder) and a Semantic Structure Consistency loss (SSC Loss). |
XIANGHENG SHAN et. al. | arxiv-cs.CV | 2024-06-14 |
| 160 | CLIP As RNN: Segment Countless Visual Concepts Without Training Endeavor Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However without fine-tuning VLMs trained under weak image-text supervision tend to make suboptimal mask predictions. To alleviate these issues we introduce a novel recurrent framework that progressively filters out irrelevant texts and enhances mask quality without training efforts. |
Shuyang Sun; Runjia Li; Philip Torr; Xiuye Gu; Siyang Li; | cvpr | 2024-06-13 |
| 161 | Unlocking The Potential of Pre-trained Vision Transformers for Few-Shot Semantic Segmentation Through Relationship Descriptors Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The recent advent of pre-trained vision transformers has unveiled a promising property: their inherent capability to group semantically related visual concepts. In this paper we explore to harnesses this emergent feature to tackle few-shot semantic segmentation a task focused on classifying pixels in a test image with a few example data. |
Ziqin Zhou; Hai-Ming Xu; Yangyang Shu; Lingqiao Liu; | cvpr | 2024-06-13 |
| 162 | Building A Strong Pre-Training Baseline for Universal 3D Large-Scale Perception Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Such inconsiderate consistency greatly hampers the promising path of reaching an universal pre-training framework: (1) The cross-scene semantic self-conflict \textit i.e. the intense collision between primitive segments of the same semantics from different scenes; (2) Lacking a globally unified bond that pushes the cross-scene semantic consistency into 3D representation learning. To address above challenges we propose a CSC framework that puts a scene-level semantic consistency in the heart bridging the connection of the similar semantic segments across various scenes. |
HAOMING CHEN et. al. | cvpr | 2024-06-13 |
| 163 | Segment Every Out-of-Distribution Object Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces a method to convert anomaly Score To segmentation Mask called S2M a simple and effective framework for OoD detection in semantic segmentation. |
Wenjie Zhao; Jia Li; Xin Dong; Yu Xiang; Yunhui Guo; | cvpr | 2024-06-13 |
| 164 | MRFS: Mutually Reinforcing Image Fusion and Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a coupled learning framework to break the performance bottleneck of infrared-visible image fusion and segmentation called MRFS. |
Hao Zhang; Xuhui Zuo; Jie Jiang; Chunchao Guo; Jiayi Ma; | cvpr | 2024-06-13 |
| 165 | SAI3D: Segment Any Instance in 3D Scenes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we introduce SAI3D a novel zero-shot 3D instance segmentation approach that synergistically leverages geometric priors and semantic cues derived from Segment Anything Model (SAM). |
YINGDA YIN et. al. | cvpr | 2024-06-13 |
| 166 | Learn to Rectify The Bias of CLIP for Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we propose to explicitly model and rectify the bias existing in CLIP to facilitate the unsupervised semantic segmentation. |
Jingyun Wang; Guoliang Kang; | cvpr | 2024-06-13 |
| 167 | Rethinking Interactive Image Segmentation with Low Latency High Quality and Diverse Prompts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work we delve deep into the architectural differences between the two types of models. |
Qin Liu; Jaemin Cho; Mohit Bansal; Marc Niethammer; | cvpr | 2024-06-13 |
| 168 | PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This divide-and-conquer strategy simplifies the algorithm development process but comes at the cost of losing an end-to-end unified solution to the problem. In this work we address this limitation by studying camera-based 3D panoptic segmentation aiming to achieve a unified occupancy representation for camera-only 3D scene understanding. |
Yuqi Wang; Yuntao Chen; Xingyu Liao; Lue Fan; Zhaoxiang Zhang; | cvpr | 2024-06-13 |
| 169 | OpenESS: Event-based Semantic Scene Understanding with Open Vocabularies Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work for the first time we synergize information from image text and event-data domains and introduce OpenESS to enable scalable ESS in an open-world annotation-efficient manner. |
Lingdong Kong; Youquan Liu; Lai Xing Ng; Benoit R. Cottereau; Wei Tsang Ooi; | cvpr | 2024-06-13 |
| 170 | Lift3D: Zero-Shot Lifting of Any 2D Vision Model to 3D Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we ask the question of whether any 2D vision model can be lifted to make 3D consistent predictions. |
MUKUND VARMA T et. al. | cvpr | 2024-06-13 |
| 171 | Image-Text Co-Decomposition for Text-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We notice that there is a discrepancy between text alignment and semantic segmentation: A text often consists of multiple semantic concepts whereas semantic segmentation strives to create semantically homogeneous segments. To address this issue we propose a novel framework Image-Text Co-Decomposition (CoDe) where the paired image and text are jointly decomposed into a set of image regions and a set of word segments respectively and contrastive learning is developed to enforce region-word alignment. |
JI-JIA WU et. al. | cvpr | 2024-06-13 |
| 172 | Density-Guided Semi-Supervised 3D Semantic Segmentation with Dual-Space Hardness Sampling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However existing point-to-point contrastive learning techniques in literature are generally sensitive to outliers resulting in insufficient modeling of the point-wise representations. To address this problem we propose a method named DDSemi for semi-supervised 3D semantic segmentation where a density-guided contrastive learning technique is explored. |
Jianan Li; Qiulei Dong; | cvpr | 2024-06-13 |
| 173 | SANeRF-HQ: Segment Anything for NeRF in High Quality Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we introduce the Segment Anything for NeRF in High Quality (SANeRF-HQ) to achieve high-quality 3D segmentation of any target object in a given scene. |
Yichen Liu; Benran Hu; Chi-Keung Tang; Yu-Wing Tai; | cvpr | 2024-06-13 |
| 174 | Hierarchical Intra-modal Correlation Learning for Label-free 3D Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However these methods usually suffer from inconsistent and noisy pseudo-labels provided by the vision language models. To address this issue we present a hierarchical intra-modal correlation learning framework that captures visual and geometric correlations in 3D scenes at three levels: intra-set intra-scene and inter-scene to help learn more compact 3D representations. |
Xin Kang; Lei Chu; Jiahao Li; Xuejin Chen; Yan Lu; | cvpr | 2024-06-13 |
| 175 | LiSA: LiDAR Localization with Semantic Awareness Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For example dynamic objects and repeating structures often negatively impact SCR. To address this problem we introduce LiSA the first method that incorporates semantic awareness into SCR to boost the localization robustness and accuracy. |
BOCHUN YANG et. al. | cvpr | 2024-06-13 |
| 176 | APSeg: Auto-Prompt Network for Cross-Domain Few-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end we propose to leverage the cutting-edge foundation model the Segment Anything Model (SAM) for generalization enhancement. |
WEIZHAO HE et. al. | cvpr | 2024-06-13 |
| 177 | Exploring Regional Clues in CLIP for Zero-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper to solve the mentioned challenge we analyze the gap between the capability of the CLIP model and the requirement of the zero-shot semantic segmentation task. |
Yi Zhang; Meng-Hao Guo; Miao Wang; Shi-Min Hu; | cvpr | 2024-06-13 |
| 178 | Unsupervised Universal Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose an Unsupervised Universal Segmentation model (U2Seg) adept at performing various image segmentation tasks—instance semantic and panoptic—using a novel unified framework. |
DANTONG NIU et. al. | cvpr | 2024-06-13 |
| 179 | GSNeRF: Generalizable Semantic Neural Radiance Fields with Enhanced 3D Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we introduce a Generalizable Semantic Neural Radiance Field (GSNeRF) which uniquely takes image semantics into the synthesis process so that both novel view images and the associated semantic maps can be produced for unseen scenes. |
Zi-Ting Chou; Sheng-Yu Huang; I-Jieh Liu; Yu-Chiang Frank Wang; | cvpr | 2024-06-13 |
| 180 | Flattening The Parent Bias: Hierarchical Semantic Segmentation in The Poincare Ball Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We find that on the new testing domains a flat (non-hierarchical) segmentation network in which the parents are inferred from the children has superior segmentation accuracy to the hierarchical approach across the board. Complementing these findings and inspired by the intrinsic properties of hyperbolic spaces we study a more principled approach to hierarchical segmentation using the Poincare ball model. |
Simon Weber; Bar?? Zöngür; Nikita Araslanov; Daniel Cremers; | cvpr | 2024-06-13 |
| 181 | UniVS: Unified and Universal Video Segmentation with Prompts As Queries Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This is mainly because generic category-specified VS tasks need to detect all objects and track them across consecutive frames while prompt-guided VS tasks require re-identifying the target with visual/text prompts throughout the entire video making it hard to handle the different tasks with the same architecture. We make an attempt to address these issues and present a novel unified VS architecture namely UniVS by using prompts as queries. |
Minghan Li; Shuai Li; Xindong Zhang; Lei Zhang; | cvpr | 2024-06-13 |
| 182 | GP-NeRF: Generalized Perception NeRF for Context-Aware 3D Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However by rendering semantic/instance labels per pixel without considering the contextual information of the rendered image these methods usually suffer from unclear boundary segmentation and abnormal segmentation of pixels within an object. To solve this problem we propose Generalized Perception NeRF (GP-NeRF) a novel pipeline that makes the widely used segmentation model and NeRF work compatibly under a unified framework for facilitating context-aware 3D scene perception. |
HAO LI et. al. | cvpr | 2024-06-13 |
| 183 | CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work we introduce a novel cost-based approach to adapt vision-language foundation models notably CLIP for the intricate task of semantic segmentation. |
SEOKJU CHO et. al. | cvpr | 2024-06-13 |
| 184 | USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The main challenge in open-vocabulary image segmentation now lies in accurately classifying these segments into text-defined categories. In this paper we introduce the Universal Segment Embedding (USE) framework to address this challenge. |
XIAOQI WANG et. al. | cvpr | 2024-06-13 |
| 185 | PEM: Prototype-based Efficient MaskFormer for Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To achieve such impressive performance these architectures employ intensive operations and require substantial computational resources which are often not available especially on edge devices. To fill this gap we propose Prototype-based Efficient MaskFormer (PEM) an efficient transformer-based architecture that can operate in multiple segmentation tasks. |
NICCOLÒ CAVAGNERO et. al. | cvpr | 2024-06-13 |
| 186 | Curriculum Point Prompting for Weakly-Supervised Referring Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nevertheless we observe that simply integrating SAM yields limited benefits and can even lead to performance regression due to the inevitable noise issues and challenges in excessive focus on object parts. In this paper we present an innovative framework Point PrompTing (PPT) incorporated with the proposed multi-source curriculum learning strategy to address these challenges. |
Qiyuan Dai; Sibei Yang; | cvpr | 2024-06-13 |
| 187 | OneFormer3D: One Transformer for Unified Point Cloud Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Thereby the similarity of all segmentation tasks and the implicit relationship between them have not been utilized effectively. This paper presents a unified simple and effective model addressing all these tasks jointly. |
Maxim Kolodiazhnyi; Anna Vorontsova; Anton Konushin; Danila Rukhovich; | cvpr | 2024-06-13 |
| 188 | Tyche: Stochastic In-Context Learning for Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: (1) We introduce a novel convolution block architecture that enables interactions among predictions. |
MARIANNE RAKIC et. al. | cvpr | 2024-06-13 |
| 189 | Open-World Semantic Segmentation Including Class Similarity Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel approach that performs accurate closed-world semantic segmentation and at the same time can identify new categories without requiring any additional training data. |
Matteo Sodano; Federico Magistri; Lucas Nunes; Jens Behley; Cyrill Stachniss; | cvpr | 2024-06-13 |
| 190 | Style Blind Domain Generalized Semantic Segmentation Via Covariance Alignment and Semantic Consistence Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However these approaches struggle with the entanglement of style and content which may lead to the unintentional removal of crucial content information causing performance degradation. This study addresses this limitation by proposing BlindNet a novel DGSS approach that blinds the style without external modules or datasets. |
Woo-Jin Ahn; Geun-Yeong Yang; Hyun-Duck Choi; Myo-Taeg Lim; | cvpr | 2024-06-13 |
| 191 | From SAM to CAMs: Exploring Segment Anything Model for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: As a remedy this paper introduces From-SAM-to-CAMs (S2C) a novel WSSS framework that directly transfers the knowledge of SAM to the classifier during the training process enhancing the quality of CAMs itself. |
Hyeokjun Kweon; Kuk-Jin Yoon; | cvpr | 2024-06-13 |
| 192 | Benchmarking Segmentation Models with Mask-Preserved Attribute Editing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Different from the previous evaluation paradigms only in consideration of global attribute variations (e.g. adverse weather) we investigate both local and global attribute variations for robustness evaluation. To achieve this we construct a mask-preserved attribute editing pipeline to edit visual attributes of real images with precise control of structural information. |
Zijin Yin; Kongming Liang; Bing Li; Zhanyu Ma; Jun Guo; | cvpr | 2024-06-13 |
| 193 | SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we propose a simple encoder-decoder named SED for open-vocabulary semantic segmentation which comprises a hierarchical encoder-based cost map generation and a gradual fusion decoder with category early rejection. |
Bin Xie; Jiale Cao; Jin Xie; Fahad Shahbaz Khan; Yanwei Pang; | cvpr | 2024-06-13 |
| 194 | Unsupervised Semantic Segmentation Through Depth-Guided Feature Correlation and Sampling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve this semantic knowledge is distilled by learning to correlate randomly sampled features from images across an entire dataset. In this work we build upon these advances by incorporating information about the structure of the scene into the training process through the use of depth information. |
Leon Sick; Dominik Engel; Pedro Hermosilla; Timo Ropinski; | cvpr | 2024-06-13 |
| 195 | MRFP: Learning Generalizable Semantic Segmentation from Sim-2-Real with Multi-Resolution Feature Perturbation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However the large domain-specific inconsistencies between simulated and real-world data pose a significant generalization challenge in semantic segmentation. In this work to alleviate this problem we propose a novel Multi-Resolution Feature Perturbation (MRFP) technique to randomize domain-specific fine-grained features and perturb style of coarse features. |
Sumanth Udupa; Prajwal Gurunath; Aniruddh Sikdar; Suresh Sundaram; | cvpr | 2024-06-13 |
| 196 | EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This technical limitation often leads to inadequate segmentation of complex objects with diverse structures. To address this gap we present a novel approach EAGLE which emphasizes object-centric representation learning for unsupervised semantic segmentation. |
Chanyoung Kim; Woojung Han; Dayun Ju; Seong Jae Hwang; | cvpr | 2024-06-13 |
| 197 | ToNNO: Tomographic Reconstruction of A Neural Network’s Output for Weakly Supervised Segmentation of 3D Medical Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel approach ToNNO which is based on the Tomographic reconstruction of a Neural Network’s Output. |
Marius Schmidt-Mengin; Alexis Benichoux; Shibeshih Belachew; Nikos Komodakis; Nikos Paragios; | cvpr | 2024-06-13 |
| 198 | SatSynth: Augmenting Image-Mask Pairs Through Diffusion Models for Aerial Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we explore the potential of generative image diffusion to address the scarcity of annotated data in earth observation tasks. |
Aysim Toker; Marvin Eisenberger; Daniel Cremers; Laura Leal-Taixé; | cvpr | 2024-06-13 |
| 199 | Traffic Scene Parsing Through The TSP6K Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However little effort has been put into improving the traffic monitoring scene understanding mainly due to the lack of specific datasets. To fill this gap we introduce a specialized traffic monitoring dataset termed TSP6K containing images from the traffic monitoring scenario with high-quality pixel-level and instance-level annotations. |
PENG-TAO JIANG et. al. | cvpr | 2024-06-13 |
| 200 | Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing methods often ignore the features of classified pixels during feature propagation. To address these limitations, this paper proposes a prototype-based feature augmentation method that leverages feature prototypes to augment scribble supervision. |
Guiyang Chan; Pengcheng Zhang; Hai Dong; Shunhui Ji; Bainian Chen; | icml | 2024-06-12 |
| 201 | BLO-SAM: Bi-level Optimization Based Finetuning of The Segment Anything Model for Overfitting-Preventing Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Current solutions to these problems, which involve finetuning SAM, often lead to overfitting, a notable issue in scenarios with very limited data, like in medical imaging. To overcome these limitations, we introduce BLO-SAM, which finetunes SAM based on bi-level optimization (BLO). |
Li Zhang; Youwei Liang; Ruiyi Zhang; Amirhosein Javadi; Pengtao Xie; | icml | 2024-06-12 |
| 202 | SimSAM: Simple Siamese Representations Based Semantic Affinity Matrix for Unsupervised Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Inspired by the non-contrastive SSL approach (SimSiam), we introduce a novel framework SIMSAM to compute the Semantic Affinity Matrix, which is significant for unsupervised image segmentation. |
Chanda Grover Kamra; Indra Deep Mastan; Nitin Kumar; Debayan Gupta; | arxiv-cs.CV | 2024-06-12 |
| 203 | A Labeled Array Distance Metric for Measuring Image Segmentation Quality Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work introduces two new distance metrics for comparing labeled arrays, which are common outputs of image segmentation algorithms. |
MARYAM BERIJANIAN et. al. | arxiv-cs.CV | 2024-06-11 |
| 204 | Beyond Bare Queries: Open-Vocabulary Object Grounding with 3D Scene Graph Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing CLIP-based open-vocabulary methods successfully perform 3D object grounding with simple (bare) queries, but cannot cope with ambiguous descriptions that demand an understanding of object relations. To tackle this problem, we propose a modular approach called BBQ (Beyond Bare Queries), which constructs 3D scene graph representation with metric and semantic edges and utilizes a large language model as a human-to-agent interface through our deductive scene reasoning algorithm. |
SERGEY LINOK et. al. | arxiv-cs.CV | 2024-06-11 |
| 205 | PanoSSC: Exploring Monocular Panoptic 3D Scene Reconstruction for Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we investigate panoptic segmentation on 3D voxel scenarios and propose an instance-aware occupancy network, PanoSSC. |
YINING SHI et. al. | arxiv-cs.CV | 2024-06-11 |
| 206 | 1st Place Winner of The 2024 Pixel-level Video Understanding in The Wild (CVPR’24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper details our research work that achieved the 1st place winner in the PVUW’24 VPS challenge, establishing state of art results in all metrics, including the Video Panoptic Quality (VPQ) and Segmentation and Tracking Quality (STQ). |
Qingfeng Liu; Mostafa El-Khamy; Kee-Bong Song; | arxiv-cs.CV | 2024-06-08 |
| 207 | USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The main challenge in open-vocabulary image segmentation now lies in accurately classifying these segments into text-defined categories. In this paper, we introduce the Universal Segment Embedding (USE) framework to address this challenge. |
XIAOQI WANG et. al. | arxiv-cs.CV | 2024-06-07 |
| 208 | 1st Place Solution for MOSE Track in CVPR 2024 PVUW Workshop: Complex Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The motivation behind the MOSE dataset is how to clearly recognize and distinguish objects in complex scenes. In this challenge, we propose a semantic embedding video object segmentation model and use the salient features of objects as query representations. |
Deshui Miao; Xin Li; Zhenyu He; Yaowei Wang; Ming-Hsuan Yang; | arxiv-cs.CV | 2024-06-06 |
| 209 | Frequency-based Matcher for Long-tailed Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Although the long-tailed phenomenon has been investigated in many fields, e.g., classification and object detection, it has not received enough attention in semantic segmentation and has become a non-negligible obstacle to applying semantic segmentation technology in autonomous driving and virtual reality. Therefore, in this work, we focus on a relatively under-explored task setting, long-tailed semantic segmentation (LTSS). |
Shan Li; Lu Yang; Pu Cao; Liulei Li; Huadong Ma; | arxiv-cs.CV | 2024-06-06 |
| 210 | Learning Semantic Traversability with Egocentric Video and Automated Annotation Strategy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present an effective methodology for training a semantic traversability estimator using egocentric videos and an automated annotation process. |
YUNHO KIM et. al. | arxiv-cs.RO | 2024-06-05 |
| 211 | Radar Spectra-Language Model for Automotive Scene Parsing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we aim to explore the semantic information contained in spectra in the context of automated driving, thereby moving towards better interpretability of radar spectra. |
Mariia Pushkareva; Yuri Feldman; Csaba Domokos; Kilian Rambach; Dotan Di Castro; | arxiv-cs.CV | 2024-06-04 |
| 212 | Zero-Shot Image Segmentation Via Recursive Normalized Cut on Diffusion Features Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we use a diffusion UNet encoder as a foundation vision encoder and introduce DiffCut, an unsupervised zero-shot segmentation method that solely harnesses the output features from the final self-attention block. |
Paul Couairon; Mustafa Shukor; Jean-Emmanuel Haugeard; Matthieu Cord; Nicolas Thome; | arxiv-cs.CV | 2024-06-04 |
| 213 | 2nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to deal with the task of video panoptic segmentation in the wild, we propose a robust integrated video panoptic segmentation solution. |
BIAO WU et. al. | arxiv-cs.CV | 2024-06-01 |
| 214 | Semi-supervised Video Semantic Segmentation Using Unreliable Pseudo Labels for PVUW2024 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we adopt semi-supervised video semantic segmentation method based on unreliable pseudo labels. |
BIAO WU et. al. | arxiv-cs.CV | 2024-06-01 |
| 215 | MCDS-VSS: Moving Camera Dynamic Scene Video Semantic Segmentation By Filtering with Self-Supervised Geometry and Motion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose MCDS-VSS, a structured filter model that learns in a self-supervised manner to estimate scene geometry and ego-motion of the camera, while also estimating the motion of external objects. |
Angel Villar-Corrales; Moritz Austermann; Sven Behnke; | arxiv-cs.CV | 2024-05-30 |
| 216 | DenseSeg: Joint Learning for Semantic Segmentation and Landmark Detection Using Dense Image-to-Shape Representation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Methods: In this work, we propose a dense image-to-shape representation that enables the joint learning of landmarks and semantic segmentation by employing a fully convolutional architecture. |
RON KEUTH et. al. | arxiv-cs.CV | 2024-05-30 |
| 217 | SemFlow: Binding Semantic Segmentation and Image Synthesis Via Rectified Flow Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For image synthesis, we propose a finite perturbation approach to enhance the diversity of generated results without changing the semantic categories. |
CHAOYANG WANG et. al. | arxiv-cs.CV | 2024-05-30 |
| 218 | View-Consistent Hierarchical 3D Segmentation Using Ultrametric Feature Fields Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we address the challenging task of lifting multi-granular and view-inconsistent image segmentations into a hierarchical and 3D-consistent representation. |
Haodi He; Colton Stearns; Adam W. Harley; Leonidas J. Guibas; | arxiv-cs.CV | 2024-05-30 |
| 219 | Reasoning3D — Grounding and Reasoning in 3D: Fine-Grained Zero-Shot Open-Vocabulary 3D Reasoning Part Segmentation Via Large Vision-Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a new task: Zero-Shot 3D Reasoning Segmentation for parts searching and localization for objects, which is a new paradigm to 3D segmentation that transcends limitations for previous category-specific 3D semantic segmentation, 3D instance segmentation, and open-vocabulary 3D segmentation. |
TIANRUN CHEN et. al. | arxiv-cs.CV | 2024-05-29 |
| 220 | Reasoning3D – Grounding and Reasoning in 3D: Fine-Grained Zero-Shot Open-Vocabulary 3D Reasoning Part Segmentation Via Large Vision-Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we introduce a new task: Zero-Shot 3D Reasoning Segmentation for parts searching and localization for objects, which is a new paradigm to 3D segmentation that … |
TIANRUN CHEN et. al. | ArXiv | 2024-05-29 |
| 221 | CRIS: Collaborative Refinement Integrated with Segmentation for Polyp Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose an approach that integrates mask refinement and binary semantic segmentation, leveraging a novel collaborative training strategy that surpasses current widely-used refinement strategies. |
Ankush Gajanan Arudkar; Bernard J. E. Evans; | arxiv-cs.CV | 2024-05-29 |
| 222 | RT-GS2: Real-Time Generalizable Semantic Segmentation for 3D Gaussian Representations of Radiance Fields Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce RT-GS2, the first generalizable semantic segmentation method employing Gaussian Splatting. |
Mihnea-Bogdan Jurca; Remco Royen; Ion Giosan; Adrian Munteanu; | arxiv-cs.CV | 2024-05-28 |
| 223 | Edge-guided and Class-balanced Active Learning for Semantic Segmentation of Aerial Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Sufficient ablation studies show that every module is indispensable. |
Lianlei Shan; Weiqiang Wang; Ke Lv; Bin Luo; | arxiv-cs.CV | 2024-05-28 |
| 224 | Zero-Shot Video Semantic Segmentation Based on Pre-Trained Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce the first zero-shot approach for Video Semantic Segmentation (VSS) based on pre-trained diffusion models. |
QIAN WANG et. al. | arxiv-cs.CV | 2024-05-27 |
| 225 | Competing for Pixels: A Self-play Algorithm for Weakly-supervised Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Leveraging reinforcement learning (RL) self-play, we propose a novel WSS method that gamifies image segmentation of a ROI. |
SHAHEER U. SAEED et. al. | arxiv-cs.CV | 2024-05-26 |
| 226 | Segformer++: Efficient Token-Merging Strategies for High-Resolution Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we explore various token merging strategies within the framework of the Segformer architecture and perform experiments on multiple semantic segmentation and human pose estimation datasets. |
Daniel Kienzle; Marco Kantonis; Robin Schön; Rainer Lienhart; | arxiv-cs.CV | 2024-05-23 |
| 227 | Multi-view Remote Sensing Image Segmentation With SAM Priors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Subsequently, we introduce SAM features via a transformer into the INF of the scene, supplementing the semantic information. |
ZIPENG QI et. al. | arxiv-cs.CV | 2024-05-23 |
| 228 | TS40K: A 3D Point Cloud Dataset of Rural Terrain and Electrical Transmission System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose TS40K, a 3D point cloud dataset that encompasses more than 40,000 Km on electrical transmission systems situated in European rural terrain. |
DIOGO LAVADO et. al. | arxiv-cs.CV | 2024-05-22 |
| 229 | BiomedParse: A Biomedical Foundation Model for Image Parsing of Everything Everywhere All at Once Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we propose BiomedParse, a biomedical foundation model for imaging parsing that can jointly conduct segmentation, detection, and recognition for 82 object types across 9 imaging modalities. |
THEODORE ZHAO et. al. | arxiv-cs.CV | 2024-05-21 |
| 230 | Universal Organizer of SAM for Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recently, a robust framework called the segment anything model (SAM) has been proven to deliver precise boundary object masks. Therefore, this paper proposes a universal organizer based on SAM, termed as UO-SAM, to enhance the mask quality of USS models. |
TINGTING LI et. al. | arxiv-cs.MM | 2024-05-19 |
| 231 | CM-UNet: Hybrid CNN-Mamba UNet for Remote Sensing Image Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose CM-UNet, comprising a CNN-based encoder for extracting local image features and a Mamba-based decoder for aggregating and integrating global information, facilitating efficient semantic segmentation of remote sensing images. |
MUSHUI LIU et. al. | arxiv-cs.CV | 2024-05-17 |
| 232 | Fourier Boundary Features Network with Wider Catchers for Glass Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We proposed the Fourier Boundary Features Network with Wider Catchers (FBWC), which might be the first attempt to utilize sufficiently wide horizontal shallow branches without vertical deepening for guiding the fine granularity segmentation boundary through primary glass semantic information. |
XIAOLIN QIN et. al. | arxiv-cs.CV | 2024-05-15 |
| 233 | CLIP with Quality Captions: A Strong Pretraining for Vision Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we find that simply improving the quality of captions in image-text datasets improves the quality of CLIP’s visual representations, resulting in significant improvement on downstream dense prediction vision tasks. |
Pavan Kumar Anasosalu Vasu; Hadi Pouransari; Fartash Faghri; Oncel Tuzel; | arxiv-cs.CV | 2024-05-14 |
| 234 | Zero Shot Context-Based Object Segmentation Using SLIP (SAM+CLIP) Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present SLIP (SAM+CLIP), an enhanced architecture for zero-shot object segmentation. |
Saaketh Koundinya Gundavarapu; Arushi Arora; Shreya Agarwal; | arxiv-cs.CV | 2024-05-12 |
| 235 | Global Motion Understanding in Large-Scale Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we show that transferring knowledge from other domains of video understanding combined with large-scale learning can improve robustness of Video Object Segmentation (VOS) under complex circumstances. |
Volodymyr Fedynyak; Yaroslav Romanus; Oles Dobosevych; Igor Babin; Roman Riazantsev; | arxiv-cs.CV | 2024-05-11 |
| 236 | Weakly-supervised Semantic Segmentation Via Dual-stream Contrastive Learning of Cross-image Contextual Information Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Weakly supervised semantic segmentation (WSSS) aims at learning a semantic segmentation model with only image-level tags. |
Qi Lai; Chi-Man Vong; | arxiv-cs.CV | 2024-05-08 |
| 237 | Few-Shot Fruit Segmentation Via Transfer Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we develop a few-shot semantic segmentation framework for infield fruits using transfer learning. |
Jordan A. James; Heather K. Manching; Amanda M. Hulse-Kemp; William J. Beksi; | arxiv-cs.CV | 2024-05-04 |
| 238 | DiffMap: Enhancing Map Segmentation with Map Prior Using Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: One prominent issue is the limited utilization of structured priors inherent in map segmentation masks. In light of this, we propose DiffMap, a novel approach specifically designed to model the structured priors of map segmentation masks using latent diffusion model. |
PEIJIN JIA et. al. | arxiv-cs.CV | 2024-05-03 |
| 239 | TinySeg: Model Optimizing Framework for Image Segmentation on Tiny Embedded Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work proposes TinySeg, a new model optimizing framework that enables memory-efficient image segmentation for tiny embedded systems. |
Byungchul Chae; Jiae Kim; Seonyeong Heo; | arxiv-cs.NE | 2024-05-03 |
| 240 | CromSS: Cross-modal Pre-training with Noisy Labels for Remote Sensing Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we propose a novel Cross-modal Sample Selection method (CromSS) that utilizes the class distributions P^{(d)}(x,c) over pixels x and classes c modelled by multiple sensors/modalities d of a given geospatial scene. |
Chenying Liu; Conrad Albrecht; Yi Wang; Xiao Xiang Zhu; | arxiv-cs.CV | 2024-05-02 |
| 241 | Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present the first comprehensive survey on XAI in semantic image segmentation. |
Rokas Gipiškis; Chun-Wei Tsai; Olga Kurasova; | arxiv-cs.CV | 2024-05-02 |
| 242 | Dual-Path Feature Aware Network for Remote Sensing Image Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation is a significant task for remote sensing interpretation, which takes advantage of contextual semantic information to classify each pixel into a specific … |
Jie Geng; Shuai Song; Wen Jiang; | IEEE Transactions on Circuits and Systems for Video … | 2024-05-01 |
| 243 | Clicks2Line: Using Lines for Interactive Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, an interactive segmentation algorithm which adaptively adopts either clicks or lines as input is proposed. |
Chaewon Lee; Chang-Su Kim; | arxiv-cs.CV | 2024-04-29 |
| 244 | CLFT: Camera-LiDAR Fusion Transformer for Semantic Segmentation in Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Specifically, the vision transformer is the novel ground-breaker that successfully brought the multi-head-attention mechanism to computer vision applications. Therefore, we propose a vision-transformer-based network to carry out camera-LiDAR fusion for semantic segmentation applied to autonomous driving. |
Junyi Gu; Mauro Bellone; Tomáš Pivoňka; Raivo Sell; | arxiv-cs.CV | 2024-04-27 |
| 245 | Semantic Segmentation Refiner for Ultrasound Applications with Zero-Shot Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we address the performance degradation of segmentation models in low-data regimes and propose a prompt-less segmentation method harnessing the ability of segmentation foundation models to segment abstract shapes. |
HEDDA COHEN INDELMAN et. al. | arxiv-cs.CV | 2024-04-25 |
| 246 | Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present PriMaPs – Principal Mask Proposals – decomposing images into semantically meaningful masks based on their feature representation. |
Oliver Hahn; Nikita Araslanov; Simone Schaub-Meyer; Stefan Roth; | arxiv-cs.CV | 2024-04-25 |
| 247 | OccFeat: Self-supervised Occupancy Feature Prediction for Pretraining BEV Segmentation Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a self-supervised pretraining method, called OccFeat, for camera-only Bird’s-Eye-View (BEV) segmentation networks. |
SOPHIA SIRKO-GALOUCHENKO et. al. | arxiv-cs.CV | 2024-04-22 |
| 248 | Clio: Real-time Task-Driven Open-Set 3D Scene Graphs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While related work implicitly chooses a level of granularity by tuning thresholds for object detection, we argue that such a choice is intrinsically task-dependent. The first contribution of this paper is to propose a task-driven 3D scene understanding problem, where the robot is given a list of tasks in natural language and has to select the granularity and the subset of objects and scene structure to retain in its map that is sufficient to complete the tasks. |
DOMINIC MAGGIO et. al. | arxiv-cs.RO | 2024-04-21 |
| 249 | Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a comprehensive survey of recent progress on annotation-efficient learning for medical image segmentation utilizing weak annotations before and in the era of foundation models. |
Yuyan Shi; Jialu Ma; Jin Yang; Shasha Wang; Yichi Zhang; | arxiv-cs.CV | 2024-04-19 |
| 250 | Show and Grasp: Few-shot Semantic Segmentation for Robot Grasping Through Zero-shot Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, this often comes at the cost of limited performance and fine-tuning is required to be effective in robot grasping scenarios. In this work, we propose to overcome all these limitations by combining the impressive generalization capability reached by foundation models with a high-performing few-shot classifier, working as a score function to select the segmentation that is closer to the support set. |
Leonardo Barcellona; Alberto Bacchin; Matteo Terreran; Emanuele Menegatti; Stefano Ghidoni; | arxiv-cs.RO | 2024-04-19 |
| 251 | Weakly Supervised LiDAR Semantic Segmentation Via Scatter Image Annotation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we propose employing scatter images to annotate LiDAR point clouds, combining a pre-trained optical flow estimation network with a foundation image segmentation model to rapidly propagate manual annotations into dense labels for both images and point clouds. |
YILONG CHEN et. al. | arxiv-cs.CV | 2024-04-19 |
| 252 | BACS: Background Aware Continual Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a Backward Background Shift Detector (BACS) to detect previously observed classes based on their distance in the latent space from the foreground centroids of previous steps. |
Mostafa ElAraby; Ali Harakeh; Liam Paull; | arxiv-cs.CV | 2024-04-19 |
| 253 | Contrastive Gaussian Clustering: Weakly Supervised 3D Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Contrastive Gaussian Clustering, a novel approach capable of provide segmentation masks from any viewpoint and of enabling 3D segmentation of the scene. |
Myrna C. Silva; Mahtab Dahaghin; Matteo Toso; Alessio Del Bue; | arxiv-cs.CV | 2024-04-19 |
| 254 | ELEV-VISION-SAM: Integrated Vision Language and Foundation Model for Automated Estimation of Building Lowest Floor Elevation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While existing methods rely on object detection, the introduction of image segmentation has broadened street view images’ utility for LFE estimation, although challenges still remain in segmentation quality and capability to distinguish front doors from other doors. To address these challenges in LFE estimation, this study integrates the Segment Anything model, a segmentation foundation model, with vision language models to conduct text-prompt image segmentation on street view images for LFE estimation. |
Yu-Hsuan Ho; Longxiang Li; Ali Mostafavi; | arxiv-cs.CV | 2024-04-18 |
| 255 | Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we develop a new model for semantic segmentation of unlabelled images, the Non-annotated Earth Observation Semantic Segmentation (NEOS) model. |
Nikolaos Dionelis; Francesco Pro; Luca Maiano; Irene Amerini; Bertrand Le Saux; | arxiv-cs.CV | 2024-04-17 |
| 256 | Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel event-based motion segmentation algorithm using a Graph Transformer Neural Network, dubbed GTNN. |
Yusra Alkendi; Rana Azzam; Sajid Javed; Lakmal Seneviratne; Yahya Zweiri; | arxiv-cs.CV | 2024-04-16 |
| 257 | ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce ECLAIR (Extended Classification of Lidar for AI Recognition), a new outdoor large-scale aerial LiDAR dataset designed specifically for advancing research in point cloud semantic segmentation. |
Iaroslav Melekhov; Anand Umashankar; Hyeong-Jin Kim; Vladislav Serkov; Dusty Argyle; | arxiv-cs.CV | 2024-04-16 |
| 258 | Vocabulary-free Image Classification and Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This assumption is impractical in scenarios with unknown or evolving semantic context. Here, we address this issue and introduce the Vocabulary-free Image Classification (VIC) task, which aims to assign a class from an unconstrained language-induced semantic space to an input image without needing a known vocabulary. |
ALESSANDRO CONTI et. al. | arxiv-cs.CV | 2024-04-16 |
| 259 | The Revenge of BiSeNet: Efficient Multi-Task Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing research has primarily concentrated on single-task settings, especially on semantic segmentation, leading to redundant efforts and specialized architectures for different tasks. To address this limitation, we propose a novel architecture for efficient multi-task image segmentation, capable of handling various segmentation tasks without sacrificing efficiency or accuracy. |
Gabriele Rosi; Claudia Cuttano; Niccolò Cavagnero; Giuseppe Averta; Fabio Cermelli; | arxiv-cs.CV | 2024-04-15 |
| 260 | Improving Referring Image Segmentation Using Vision-Aware Text Features Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This over-reliance on visual features can lead to suboptimal results, especially in complex scenarios where text prompts are ambiguous or context-dependent. To overcome these challenges, we present a novel framework VATEX to improve referring image segmentation by enhancing object and context understanding with Vision-Aware Text Feature. |
HAI NGUYEN-TRUONG et. al. | arxiv-cs.CV | 2024-04-12 |
| 261 | Gaga: Group Any Gaussians Via 3D-aware Memory Bank Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Gaga, a framework that reconstructs and segments open-world 3D scenes by leveraging inconsistent 2D masks predicted by zero-shot segmentation models. |
Weijie Lyu; Xueting Li; Abhijit Kundu; Yi-Hsuan Tsai; Ming-Hsuan Yang; | arxiv-cs.CV | 2024-04-11 |
| 262 | Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing approaches often rely on impractical supervised pre-training or access to additional pre-trained networks. In this work, we propose a strong baseline for training-free OVSS, termed Neighbour-Aware CLIP (NACLIP), representing a straightforward adaptation of CLIP tailored for this scenario. |
Sina Hajimiri; Ismail Ben Ayed; Jose Dolz; | arxiv-cs.CV | 2024-04-11 |
| 263 | Exploiting Object-based and Segmentation-based Semantic Features for Deep Learning-based Indoor Scene Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To overcome such issues, gathering semantic information has been shown to be a promising source of information towards a more complete and discriminative feature representation of indoor scenes. Therefore, the work described in this paper uses both semantic information, obtained from object detection, and semantic segmentation techniques. |
Ricardo Pereira; Luís Garrote; Tiago Barros; Ana Lopes; Urbano J. Nunes; | arxiv-cs.CV | 2024-04-11 |
| 264 | O2V-Mapping: Online Open-Vocabulary Mapping with Neural Implicit Representation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For the purpose of preserving consistency in 3D object properties across different viewpoints, we propose a spatial adaptive voxel adjustment mechanism and a multi-view weight selection method. |
MUER TIE et. al. | arxiv-cs.CV | 2024-04-10 |
| 265 | QueSTMaps: Queryable Semantic Topological Maps for 3D Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a two-step pipeline. |
YASH MEHAN et. al. | arxiv-cs.CV | 2024-04-09 |
| 266 | DaF-BEVSeg: Distortion-aware Fisheye Camera Based Bird’s Eye View Segmentation with Occlusion Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We extend the model with an occlusion reasoning module, which is critical for estimating in BEV space. |
Senthil Yogamani; David Unger; Venkatraman Narayanan; Varun Ravi Kumar; | arxiv-cs.CV | 2024-04-09 |
| 267 | Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero Shot Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Specifically, we propose a simple unified framework, SaLIP, for organ segmentation. |
SIDRA ALEEM et. al. | arxiv-cs.CV | 2024-04-09 |
| 268 | Evaluating The Efficacy of Cut-and-Paste Data Augmentation in Semantic Segmentation for Satellite Imagery Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to mitigate those issues, our study explores the effectiveness of a Cut-and-Paste augmentation technique for semantic segmentation in satellite images. We adapt this augmentation, which usually requires labeled instances, to the case of semantic segmentation. |
Ionut M. Motoi; Leonardo Saraceni; Daniele Nardi; Thomas A. Ciarfuglia; | arxiv-cs.CV | 2024-04-08 |
| 269 | D2SL: Decouple Defogging and Semantic Learning for Foggy Domain-Adaptive Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite making some progress, there are still two main drawbacks: (1) the coupling of segmentation and defogging feature representations, resulting in a decrease in semantic representation capability, and (2) the failure to leverage real fog priors in unlabeled foggy data, leading to insufficient model generalization ability. To address these issues, we propose a novel training framework, Decouple Defogging and Semantic learning, called D2SL, aiming to alleviate the adverse impact of defogging tasks on the final segmentation task. |
Xuan Sun; Zhanfu An; Yuyu Liu; | arxiv-cs.CV | 2024-04-07 |
| 270 | HawkDrive: A Transformer-driven Visual Perception System for Autonomous Driving in Night Scene Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Many established vision perception systems for autonomous driving scenarios ignore the influence of light conditions, one of the key elements for driving safety. To address this problem, we present HawkDrive, a novel perception system with hardware and software solutions. |
Ziang Guo; Stepan Perminov; Mikhail Konenkov; Dzmitry Tsetserukou; | arxiv-cs.CV | 2024-04-06 |
| 271 | Panoptic Perception: A Novel Task and Fine-grained Dataset for Universal Remote Sensing Image Interpretation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Panoptic Perception, a novel task and a new fine-grained dataset (FineGrip) to achieve a more thorough and universal interpretation for RSIs. |
DANPEI ZHAO et. al. | arxiv-cs.CV | 2024-04-06 |
| 272 | Frequency Decomposition-Driven Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: It is still challenging to retain cross-domain local spatial details and global contextual semantics simultaneously, which is crucial for the RS image semantic segmentation task. To address these problems, we propose novel high/low-frequency decomposition (HLFD) techniques to guide representation alignment in cross-domain semantic segmentation. |
Xianping Ma; Xiaokang Zhang; Xingchen Ding; Man-On Pun; Siwei Ma; | arxiv-cs.CV | 2024-04-06 |
| 273 | Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce Sigma, a Siamese Mamba network for multi-modal semantic segmentation, utilizing the Selective Structured State Space Model, Mamba. |
ZIFU WAN et. al. | arxiv-cs.CV | 2024-04-05 |
| 274 | Background Noise Reduction of Attention Map for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The proposed method successfully reduces background noise, leading to improved accuracy of pseudo labels. |
Izumi Fujimori; Masaki Oono; Masami Shishibori; | arxiv-cs.CV | 2024-04-04 |
| 275 | OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Indeed, point cloud and 3D meshes typically have a lower resolution than images and the reconstructed 3D scene geometry might not project well to the underlying 2D image sequences used to compute pixel-aligned CLIP features. To address these challenges, we propose OpenNeRF which naturally operates on posed images and directly encodes the VLM features within the NeRF. |
FRANCIS ENGELMANN et. al. | arxiv-cs.CV | 2024-04-04 |
| 276 | Flattening The Parent Bias: Hierarchical Semantic Segmentation in The Poincaré Ball Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find that on the new testing domains, a flat (non-hierarchical) segmentation network, in which the parents are inferred from the children, has superior segmentation accuracy to the hierarchical approach across the board. Complementing these findings and inspired by the intrinsic properties of hyperbolic spaces, we study a more principled approach to hierarchical segmentation using the Poincar\’e ball model. |
Simon Weber; Barış Zöngür; Nikita Araslanov; Daniel Cremers; | arxiv-cs.CV | 2024-04-04 |
| 277 | Segmentation of Road Negative Obstacles Based on Dual Semantic-Feature Complementary Fusion for Autonomous Driving Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Segmentation of road negative obstacles (i.e., potholes and cracks) is important to the safety of autonomous driving. Although existing RGB-D fusion networks could achieve … |
Zhen Feng; Yanning Guo; Yuxiang Sun; | IEEE Transactions on Intelligent Vehicles | 2024-04-01 |
| 278 | Semantic Hierarchy-Aware Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Humans are able to recognize structured relations in observation, allowing us to decompose complex scenes into simpler parts and abstract the visual world at multiple levels. … |
Liulei Li; Wenguan Wang; Tianfei Zhou; Ruijie Quan; Yi Yang; | IEEE Transactions on Pattern Analysis and Machine … | 2024-04-01 |
| 279 | Training-Free Semantic Segmentation Via LLM-Supervision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a new approach to text-supervised semantic segmentation using supervision by a large language model (LLM) that does not require extra training. |
Wenfang Sun; Yingjun Du; Gaowen Liu; Ramana Kompella; Cees G. M. Snoek; | arxiv-cs.CV | 2024-03-31 |
| 280 | MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel framework, called MedCLIP-SAM that combines CLIP and SAM models to generate segmentation of clinical scans using text prompts in both zero-shot and weakly supervised settings. |
Taha Koleilat; Hojat Asgariandehkordi; Hassan Rivaz; Yiming Xiao; | arxiv-cs.CV | 2024-03-29 |
| 281 | Segmentation Re-thinking Uncertainty Estimation Metrics for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, our investigation identifies three core deficiencies within the PAvPU framework and proposes robust solutions aimed at refining the metric. By addressing these issues, we aim to enhance the reliability and applicability of uncertainty quantification, especially in scenarios that demand high levels of safety and accuracy, thus contributing to the advancement of semantic segmentation methodologies in critical applications. |
Qitian Ma; Shyam Nanda Rai; Carlo Masone; Tatiana Tommasi; | arxiv-cs.AI | 2024-03-28 |
| 282 | I2CKD : Intra- and Inter-Class Knowledge Distillation for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a new knowledge distillation method tailored for image semantic segmentation, termed Intra- and Inter-Class Knowledge Distillation (I2CKD). |
Ayoub Karine; Thibault Napoléon; Maher Jridi; | arxiv-cs.CV | 2024-03-27 |
| 283 | SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imaging Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Few-shot learning segmentation methods are typically designed for specific modalities of data and cannot be directly transferred for use with another modality. Therefore, we introduce SegICL, a novel approach leveraging In-Context Learning (ICL) for image segmentation. |
LINGDONG SHEN et. al. | arxiv-cs.CV | 2024-03-25 |
| 284 | SatSynth: Augmenting Image-Mask Pairs Through Diffusion Models for Aerial Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we explore the potential of generative image diffusion to address the scarcity of annotated data in earth observation tasks. |
Aysim Toker; Marvin Eisenberger; Daniel Cremers; Laura Leal-Taixé; | arxiv-cs.CV | 2024-03-25 |
| 285 | Learning Generalized Segmentation for Foggy-Scenes By Bi-directional Wavelet Guidance Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Learning scene semantics that can be well generalized to foggy conditions is important for safety-crucial applications such as autonomous driving. Existing methods need both … |
Qi Bi; Shaodi You; Theo Gevers; | AAAI Conference on Artificial Intelligence | 2024-03-24 |
| 286 | SM2C: Boost The Semi-supervised Segmentation for Medical Image By Using Meta Pseudo Labels and Mixed Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we introduce a novel method called Scaling-up Mix with Multi-Class (SM2C). |
Yifei Wang; Chuhong Zhu; | arxiv-cs.CV | 2024-03-24 |
| 287 | WeatherProof: Leveraging Language Guidance for Semantic Segmentation in Adverse Weather Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a method to infer semantic segmentation maps from images captured under adverse weather conditions. |
BLAKE GELLA et. al. | arxiv-cs.CV | 2024-03-21 |
| 288 | MTP: Advancing Remote Sensing Foundation Model Via Multitask Pretraining Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Foundation models have reshaped the landscape of remote sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing … |
DI WANG et. al. | IEEE Journal of Selected Topics in Applied Earth … | 2024-03-20 |
| 289 | MTP: Advancing Remote Sensing Foundation Model Via Multi-Task Pretraining Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, transferring the pretrained models to downstream tasks may encounter task discrepancy due to their formulation of pretraining as image classification or object discrimination tasks. In this study, we explore the Multi-Task Pretraining (MTP) paradigm for RS foundation models to address this issue. |
DI WANG et. al. | arxiv-cs.CV | 2024-03-20 |
| 290 | Reflectivity Is All You Need!: Advancing LiDAR Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Building upon our previous work, this paper explores the advantages of employing calibrated intensity (also referred to as reflectivity) within learning-based LiDAR semantic segmentation frameworks. |
Kasi Viswanath; Peng Jiang; Srikanth Saripalli; | arxiv-cs.CV | 2024-03-19 |
| 291 | Opti-Acoustic Semantic SLAM with Unknown Objects in Underwater Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents an object-based semantic SLAM method for underwater environments that can identify, localize, classify, and map a wide variety of marine objects without a priori knowledge of the object classes present in the scene. |
Kurran Singh; Jungseok Hong; Nicholas R. Rypkema; John J. Leonard; | arxiv-cs.RO | 2024-03-19 |
| 292 | BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Semantic scene segmentation from a bird’s-eye-view (BEV) perspective plays a crucial role in facilitating planning and decision-making for mobile robots. Although recent … |
JONAS SCHRAMM et. al. | ArXiv | 2024-03-18 |
| 293 | TTT-KD: Test-Time Training for 3D Semantic Segmentation Through Knowledge Distillation from Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose the first TTT method for 3D semantic segmentation, TTT-KD, which models Knowledge Distillation (KD) from foundation models (e.g. DINOv2) as a self-supervised objective for adaptation to distribution shifts at test-time. |
Lisa Weijler; Muhammad Jehanzeb Mirza; Leon Sick; Can Ekkazan; Pedro Hermosilla; | arxiv-cs.CV | 2024-03-18 |
| 294 | Segment Any Object Model (SAOM): Real-to-Simulation Fine-Tuning Strategy for Multi-Class Multi-Instance Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To allow our Segment Any Object Model (SAOM) to work in the everything mode, we propose the novel nearest neighbour assignment method, updating point embeddings for each ground-truth mask. |
MARIIA KHAN et. al. | arxiv-cs.CV | 2024-03-15 |
| 295 | TransLandSeg: A Transfer Learning Approach for Landslide Semantic Segmentation Based on Vision Foundation Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose TransLandSeg, which is a transfer learning approach for landslide semantic segmentation based on a vision foundation model (VFM). |
CHANGHONG HOU et. al. | arxiv-cs.CV | 2024-03-15 |
| 296 | Annotation Free Semantic Segmentation with Vision Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we generate free annotations for any semantic segmentation dataset using existing foundation models. |
Soroush Seifi; Daniel Olmeda Reino; Fabien Despinoy; Rahaf Aljundi; | arxiv-cs.CV | 2024-03-14 |
| 297 | Customizing Segmentation Foundation Model Via Prompt Learning for Instance Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, despite its strength, SAM faces two key limitations when applied to customized instance segmentation that segments specific objects or those in unique environments not typically present in the training data: 1) the ambiguity inherent in input prompts and 2) the necessity for extensive additional training to achieve optimal segmentation. To address these challenges, we propose a novel method, customized instance segmentation via prompt learning tailored to SAM. |
Hyung-Il Kim; Kimin Yun; Jun-Seok Yun; Yuseok Bae; | arxiv-cs.CV | 2024-03-14 |
| 298 | When Semantic Segmentation Meets Frequency Aliasing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing research only separates an image into easy and hard regions and empirically observes the latter are associated with object boundaries. In this paper, we conduct a comprehensive analysis of hard pixel errors, categorizing them into three types: false responses, merging mistakes, and displacements. |
Linwei Chen; Lin Gu; Ying Fu; | arxiv-cs.CV | 2024-03-13 |
| 299 | Average Calibration Error: A Differentiable Loss for Improved Reliability in Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose to use marginal L1 average calibration error (mL1-ACE) as a novel auxiliary loss function to improve pixel-wise calibration without compromising segmentation quality. |
Theodore Barfoot; Luis Garcia-Peraza-Herrera; Ben Glocker; Tom Vercauteren; | arxiv-cs.CV | 2024-03-11 |
| 300 | Forest Inspection Dataset for Aerial Semantic Segmentation and Depth Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Deep learning algorithms must be trained on large amounts of data to output accurate interpretations, but ground truth recordings of annotated forest imagery are not available. To solve this problem, we introduce a new large aerial dataset for forest inspection which contains both real-world and virtual recordings of natural environments, with densely annotated semantic segmentation labels and depth maps, taken in different illumination conditions, at various altitudes and recording angles. |
Bianca-Cerasela-Zelia Blaga; Sergiu Nedevschi; | arxiv-cs.CV | 2024-03-11 |
| 301 | Refining Segmentation On-the-Fly: An Interactive Framework for Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Concretely, we presents the first interactive framework for point cloud semantic segmentation, named InterPCSeg, which seamlessly integrates with off-the-shelf semantic segmentation networks without offline re-training, enabling it to run in an on-the-fly manner. |
Peng Zhang; Ting Wu; Jinsheng Sun; Weiqing Li; Zhiyong Su; | arxiv-cs.CV | 2024-03-10 |
| 302 | Multi-Grained Cross-modal Alignment for Learning Open-vocabulary Semantic Segmentation from Text Supervision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a Multi-Grained Cross-modal Alignment (MGCA) framework, which explicitly learns pixel-level alignment along with object- and region-level alignment to bridge the granularity gap without any dense annotations. |
Yajie Liu; Pu Ge; Qingjie Liu; Di Huang; | arxiv-cs.CV | 2024-03-06 |
| 303 | Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Prior works have commonly used an off-line heuristic thresholding process that combines the CAM maps with off-the-shelf saliency maps produced by a general pre-trained saliency model to produce more accurate pseudo-segmentation labels. We propose AuxSegNet+, a weakly supervised auxiliary learning framework to explore the rich information from these saliency maps and the significant inter-task correlation between saliency detection and semantic segmentation. |
LIAN XU et. al. | arxiv-cs.CV | 2024-03-02 |
| 304 | Building Energy Efficient Semantic Segmentation in Intelligent Edge Computing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation is a critical area in computer vision, which needs voluminous image data streaming from user devices. Usually, it is challenging to process semantic … |
Xingyu Yuan; He Li; K. Ota; M. Dong; | IEEE Transactions on Green Communications and Networking | 2024-03-01 |
| 305 | Contrastive Learning-based Knowledge Distillation for RGB-thermal Urban Scene Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xiaodong Guo; Wujie Zhou; Tong Liu; | Knowl. Based Syst. | 2024-03-01 |
| 306 | PEM: Prototype-based Efficient MaskFormer for Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To achieve such impressive performance, these architectures employ intensive operations and require substantial computational resources, which are often not available, especially on edge devices. To fill this gap, we propose Prototype-based Efficient MaskFormer (PEM), an efficient transformer-based architecture that can operate in multiple segmentation tasks. |
NICCOLÒ CAVAGNERO et. al. | arxiv-cs.CV | 2024-02-29 |
| 307 | YOLO-MED : Multi-Task Interaction Network for Biomedical Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose an efficient end-to-end multi-task network capable of concurrently performing object detection and semantic segmentation called YOLO-Med. |
SUIZHI HUANG et. al. | arxiv-cs.CV | 2024-02-29 |
| 308 | FusionVision: A Comprehensive Approach of 3D Object Reconstruction and Segmentation from RGB-D Cameras Using YOLO and Fast Segment Anything Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In the realm of computer vision, the integration of advanced techniques into the processing of RGB-D camera inputs poses a significant challenge, given the inherent complexities arising from diverse environmental conditions and varying object appearances. Therefore, this paper introduces FusionVision, an exhaustive pipeline adapted for the robust 3D segmentation of objects in RGB-D imagery. |
Safouane El Ghazouali; Youssef Mhirit; Ali Oukhrid; Umberto Michelucci; Hichem Nouira; | arxiv-cs.CV | 2024-02-29 |
| 309 | One Model to Use Them All: Training A Segmentation Model with Complementary Datasets Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a method to combine multiple partially annotated datasets, which provide complementary annotations, into one model, enabling better scene segmentation and the use of multiple readily available datasets. |
ALEXANDER C. JENKE et. al. | arxiv-cs.CV | 2024-02-29 |
| 310 | Spannotation: Enhancing Semantic Segmentation for Autonomous Navigation with Efficient Image Annotation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unlike other popular annotation tools that requires about 40 seconds to annotate an image for semantic segmentation in a typical navigation task, Spannotation achieves similar result in about 6.03 seconds. The tools utility was validated through the utilization of its generated masks to train a U-Net model which achieved a validation accuracy of 98.27% and mean Intersection Over Union (mIOU) of 96.66%. |
Samuel O. Folorunsho; William R. Norris; | arxiv-cs.CV | 2024-02-28 |
| 311 | DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present DFormer, a novel RGB-D pretraining framework to learn transferable representations for RGB-D segmentation tasks. |
BOWEN YIN et. al. | iclr | 2024-02-26 |
| 312 | CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we embark on an in-depth analysis of the region-language alignment in CLIP models, which is essential for downstream open-vocabulary dense prediction tasks. |
SIZE WU et. al. | iclr | 2024-02-26 |
| 313 | BLO-SAM: Bi-level Optimization Based Overfitting-Preventing Finetuning of SAM Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Current solutions to these problems, which involve finetuning SAM, often lead to overfitting, a notable issue in scenarios with very limited data, like in medical imaging. To overcome these limitations, we introduce BLO-SAM, which finetunes SAM based on bi-level optimization (BLO). |
Li Zhang; Youwei Liang; Ruiyi Zhang; Amirhosein Javadi; Pengtao Xie; | arxiv-cs.CV | 2024-02-26 |
| 314 | P2Seg: Pointly-supervised Segmentation Via Mutual Distillation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we design a Mutual Distillation Module (MDM) to leverage the complementary strengths of both instance position and semantic information and achieve accurate instance-level object perception. |
ZIPENG WANG et. al. | iclr | 2024-02-26 |
| 315 | Personalize Segment Anything Model with One Shot IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a training-free Personalization approach for SAM, termed PerSAM.To demonstrate our efficacy, we construct a new dataset, PerSeg, for the evaluation of personalized object segmentation, and also test our methods on various one-shot image and video segmentation benchmarks. |
RENRUI ZHANG et. al. | iclr | 2024-02-26 |
| 316 | EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, generating fine-grained segmentation masks with diffusion models often requires additional training on annotated datasets, leaving it unclear to what extent pre-trained diffusion models alone understand the semantic relations of their generated images. To address this question, we leverage the semantic knowledge extracted from Stable Diffusion (SD) and aim to develop an image segmentor capable of generating fine-grained segmentation maps without any additional training. |
Koichi Namekata; Amirmojtaba Sabour; Sanja Fidler; Seung Wook Kim; | iclr | 2024-02-26 |
| 317 | Placing Objects in Context Via Inpainting for Out-of-distribution Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the Placing Objects in Context (POC) pipeline to realistically add any object into any image via diffusion models. |
Pau de Jorge; Riccardo Volpi; Puneet K. Dokania; Philip H. S. Torr; Gregory Rogez; | arxiv-cs.CV | 2024-02-26 |
| 318 | Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While it exhibits remarkable zero-shot generalization in typical scenarios, its advantage diminishes when applied to specialized domains like medical imagery and remote sensing. To address this limitation, this paper introduces Conv-LoRA, a simple yet effective parameter-efficient fine-tuning approach. |
Zihan Zhong; Zhiqiang Tang; Tong He; Haoyang Fang; Chun Yuan; | iclr | 2024-02-26 |
| 319 | OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Indeed, point cloud and 3D meshes typically have a lower resolution than images and the reconstructed 3D scene geometry might not project well to the underlying 2D image sequences used to compute pixel-aligned CLIP features. To address these challenges, we propose OpenNeRF which naturally operates on posed images and directly encodes the VLM features within the NeRF. |
Francis Engelmann; Fabian Manhardt; Michael Niemeyer; Keisuke Tateno; Federico Tombari; | iclr | 2024-02-26 |
| 320 | Task Specific Pretraining with Noisy Labels for Remote Sensing Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose to exploit noisy semantic segmentation maps for model pretraining. |
Chenying Liu; Conrad M Albrecht; Yi Wang; Xiao Xiang Zhu; | arxiv-cs.CV | 2024-02-25 |
| 321 | QIS : Interactive Segmentation Via Quasi-Conformal Mappings Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose the quasi-conformal interactive segmentation (QIS) model, which incorporates user input in the form of positive and negative clicks. |
Han Zhang; Daoping Zhang; Lok Ming Lui; | arxiv-cs.CV | 2024-02-22 |
| 322 | DeiSAM: Segment Anything with Deictic Prompting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, deep learning approaches cannot reliably interpret such deictic representations due to their lack of reasoning capabilities in complex scenarios. To remedy this issue, we propose DeiSAM — a combination of large pre-trained neural networks with differentiable logic reasoners — for deictic promptable segmentation. |
HIKARU SHINDO et. al. | arxiv-cs.LG | 2024-02-21 |
| 323 | ISCUTE: Instance Segmentation of Cables Using Text Embedding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a foundation model-based DLO instance segmentation technique that is text-promptable and user-friendly. |
Shir Kozlovsky; Omkar Joglekar; Dotan Di Castro; | arxiv-cs.CV | 2024-02-19 |
| 324 | Object-level Geometric Structure Preserving for Natural Image Stitching Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we endeavour to safeguard the overall OBJect-level structures within images based on Global Similarity Prior (OBJ-GSP), on the basis of good alignment performance. |
Wenxiao Cai; Wankou Yang; | arxiv-cs.CV | 2024-02-19 |
| 325 | Real-time 3D Semantic Scene Perception for Egocentric Robots with Binocular Vision Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present an end-to-end pipeline with instance segmentation, feature matching, and point-set registration for egocentric robots with binocular vision, and demonstrate the robot’s grasping capability through the proposed pipeline. |
K. Nguyen; T. Dang; M. Huber; | arxiv-cs.RO | 2024-02-19 |
| 326 | Semantically-aware Neural Radiance Fields for Visual Scene Understanding: A Comprehensive Review Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This review thoroughly examines the role of semantically-aware Neural Radiance Fields (NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. |
Thang-Anh-Quan Nguyen; Amine Bourki; Mátyás Macudzinski; Anthony Brunel; Mohammed Bennamoun; | arxiv-cs.CV | 2024-02-16 |
| 327 | BEFUnet: A Hybrid CNN-Transformer Architecture for Precise Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While transformers have achieved state-of-the-art results in natural language processing and image recognition, they face challenges in medical image segmentation due to image locality and translational invariance issues. To address these challenges, this paper proposes an innovative U-shaped network called BEFUnet, which enhances the fusion of body and edge information for precise medical image segmentation. |
Omid Nejati Manzari; Javad Mirzapour Kaleybar; Hooman Saadat; Shahin Maleki; | arxiv-cs.CV | 2024-02-13 |
| 328 | Moving Object Proposals with Deep Learned Optical Flow for Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a state of art architecture of neural networks to accurately and efficiently get the moving object proposals (MOP). |
Ge Shi; Zhili Yang; | arxiv-cs.CV | 2024-02-13 |
| 329 | Unsupervised Discovery of Object-Centric Neural Fields Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This limitation stems from their object representations, which entangle objects’ intrinsic attributes like shape and appearance with extrinsic, viewer-centric properties such as their 3D location. To address this bottleneck, we propose Unsupervised discovery of Object-Centric neural Fields (uOCF). |
Rundong Luo; Hong-Xing Yu; Jiajun Wu; | arxiv-cs.CV | 2024-02-11 |
| 330 | Hybridnet for Depth Estimation and Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, depth estimation and semantic segmentation are addressed together from a single input image through a hybrid convolutional network. |
Dalila Sánchez-Escobedo; Xiao Lin; Josep R. Casas; Montse Pardàs; | arxiv-cs.CV | 2024-02-09 |
| 331 | Early Fusion of Features for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel segmentation framework that integrates a classifier network with a reverse HRNet architecture for efficient image segmentation. |
Anupam Gupta; Ashok Krishnamurthy; Lisa Singh; | arxiv-cs.CV | 2024-02-08 |
| 332 | Multi-Scale Semantic Segmentation with Modified MBConv Blocks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel adaptation of MBConv blocks specifically tailored for semantic segmentation. |
Xi Chen; Yang Cai; Yuan Wu; Bo Xiong; Taesung Park; | arxiv-cs.CV | 2024-02-07 |
| 333 | On The Effect of Image Resolution on Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we demonstrate that a streamlined model capable of directly producing high-resolution segmentations can match the performance of more complex systems that generate lower-resolution results. |
Ritambhara Singh; Abhishek Jain; Pietro Perona; Shivani Agarwal; Junfeng Yang; | arxiv-cs.CV | 2024-02-07 |
| 334 | Instance Segmentation XXL-CT Challenge of A Historic Airplane Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The challenge aimed to explore automatic or interactive instance segmentation methods for an efficient delineation of the different aircraft components, such as screws, rivets, metal sheets or pressure tubes. We report the organization and outcome of this challenge and describe the capabilities and limitations of the submitted segmentation methods. |
ROLAND GRUBER et. al. | arxiv-cs.CV | 2024-02-05 |
| 335 | Applying Unsupervised Semantic Segmentation to High-Resolution UAV Imagery for Enhanced Road Scene Parsing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: There are two challenges presented in parsing road scenes from UAV images: the complexity of processing high-resolution images and the dependency on extensive manual annotations required by traditional supervised deep learning methods to train robust and accurate models. In this paper, a novel unsupervised road parsing framework that leverages advancements in vision language models with fundamental computer vision techniques is introduced to address these critical challenges. |
Zihan Ma; Yongshang Li; Ronggui Ma; Chen Liang; | arxiv-cs.CV | 2024-02-05 |
| 336 | Delving Into Decision-based Black-box Attacks on Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present the first exploration of black-box decision-based attacks on semantic segmentation. |
ZHAOYU CHEN et. al. | arxiv-cs.CV | 2024-02-02 |
| 337 | Vision-enhanced Peg-in-Hole for Automotive Body Parts Using Semantic Image Segmentation and Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts View |
M. SILEO et. al. | Eng. Appl. Artif. Intell. | 2024-02-01 |
| 338 | An Adaptive Post-Processing Network With The Global-Local Aggregation for Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Current semantic segmentation methods mainly focus on modeling the context of the global image to obtain high-quality segmentation results. However, they ignore the role of local … |
GUILIN ZHU et. al. | IEEE Transactions on Circuits and Systems for Video … | 2024-02-01 |
| 339 | Small Target Augmentation for Urban Remote Sensing Image Real-Time Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Urban remote sensing (URS) image segmentation is very important for many applications from automotive navigation to infrastructure monitoring, and urban management. There are … |
Shasha Ren; Qiong Liu; | IEEE Transactions on Intelligent Transportation Systems | 2024-02-01 |
| 340 | Multi-Level Medical Image Segmentation Network Based on Multi-Scale and Context Information Fusion Strategy Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Accurate segmentation of human tissue structure from medical images is one of the critical links in medical image diagnosis. However, due to the medical image scale of different … |
DAYU TAN et. al. | IEEE Transactions on Emerging Topics in Computational … | 2024-02-01 |
| 341 | SubPipe: A Submarine Pipeline Inspection Dataset for Segmentation and Visual-inertial Localization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents SubPipe, an underwater dataset for SLAM, object detection, and image segmentation. |
OLAYA ÁLVAREZ-TUÑÓN et. al. | arxiv-cs.RO | 2024-01-31 |
| 342 | Towards Image Semantics and Syntax Sequence Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To learn the image grammar relative to a class of visual objects/scenes, we propose a weakly supervised two-stage approach. |
Chun Tao; Timur Ibrayev; Kaushik Roy; | arxiv-cs.CV | 2024-01-30 |
| 343 | CAFCT: Contextual and Attentional Feature Fusions of Convolutional Neural Networks and Transformer for Liver Tumor Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Contextual and Attentional feature Fusions enhanced Convolutional Neural Network (CNN) and Transformer hybrid network (CAFCT) model for liver tumor segmentation. |
Ming Kang; Chee-Ming Ting; Fung Fung Ting; Raphaël Phan; | arxiv-cs.CV | 2024-01-30 |
| 344 | Synthetic Data Enables Faster Annotation and Robust Segmentation for Multi-object Grasping in Clutter Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a synthetic data generation method that minimizes human intervention and makes downstream image segmentation algorithms more robust by combining a generated synthetic dataset with a smaller real-world dataset (hybrid dataset). |
Dongmyoung Lee; Wei Chen; Nicolas Rojas; | arxiv-cs.CV | 2024-01-24 |
| 345 | Self-Supervised Vision Transformers Are Efficient Segmentation Learners for Imperfect Labels Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study demonstrates a cost-effective approach to semantic segmentation using self-supervised vision transformers (SSVT). |
Seungho Lee; Seoungyoon Kang; Hyunjung Shim; | arxiv-cs.CV | 2024-01-23 |
| 346 | DatUS^2: Data-driven Unsupervised Semantic Segmentation with Pre-trained Self-supervised Vision Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, unsupervised dense semantic segmentation has not been explored as a downstream task, which can utilize and evaluate the quality of semantic information introduced in patch-level feature representations during self-supervised training of a vision transformer. Therefore, this paper proposes a novel data-driven approach for unsupervised semantic segmentation (DatUS^2) as a downstream task. |
Sonal Kumar; Arijit Sur; Rashmi Dutta Baruah; | arxiv-cs.CV | 2024-01-23 |
| 347 | SemPLeS: Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the issues, we propose a Semantic Prompt Learning for WSSS (SemPLeS) framework, which learns to effectively prompt the CLIP latent space to enhance the semantic alignment between the segmented regions and the target object categories. |
Ci-Siang Lin; Chien-Yi Wang; Yu-Chiang Frank Wang; Min-Hung Chen; | arxiv-cs.CV | 2024-01-22 |
| 348 | Concealed Object Segmentation with Hierarchical Coherence Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite achieving remarkable success, existing COS segmenters still struggle to achieve complete segmentation results in extremely concealed scenarios. In this paper, we propose a Hierarchical Coherence Modeling (HCM) segmenter for COS, aiming to address this incomplete segmentation limitation. |
Fengyang Xiao; Pan Zhang; Chunming He; Runze Hu; Yutao Liu; | arxiv-cs.CV | 2024-01-22 |
| 349 | MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by recent advances in meta learning, we argue that rather than struggling to tolerate noise hidden behind clean labels passively, a more feasible solution would be to find out the noisy regions actively, so as to simply ignore them during model optimization. With this in mind, this work presents a novel meta learning based semantic segmentation method, MetaSeg, that comprises a primary content-aware meta-net (CAM-Net) to sever as a noise indicator for an arbitrary segmentation model counterpart. |
SHENWANG JIANG et. al. | arxiv-cs.CV | 2024-01-22 |
| 350 | S$^3$M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hence, in this article, we introduce S$^3$M-Net, a novel joint learning framework developed to perform semantic segmentation and stereo matching simultaneously. |
ZHIYUAN WU et. al. | arxiv-cs.CV | 2024-01-21 |
| 351 | S$^{3}$M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation and stereo matching are two essential components of 3D environmental perception systems for autonomous driving. Nevertheless, conventional approaches often … |
ZHIYUAN WU et. al. | IEEE Transactions on Intelligent Vehicles | 2024-01-21 |
| 352 | Spatial Structure Constraints for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose spatial structure constraints (SSC) for weakly supervised semantic segmentation to alleviate the unwanted object over-activation of attention expansion. |
TAO CHEN et. al. | arxiv-cs.CV | 2024-01-20 |
| 353 | XAI-Enhanced Semantic Segmentation Models for Visual Quality Inspection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a framework to bolster visual quality inspection by using CAM-based explanations to refine semantic segmentation models. |
Tobias Clement; Truong Thanh Hung Nguyen; Mohamed Abdelaal; Hung Cao; | arxiv-cs.CV | 2024-01-18 |
| 354 | RAP-SAM: Towards Real-Time All-Purpose Segment Anything Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: It contains three different tasks, including interactive segmentation, panoptic segmentation, and video segmentation. We aim to use one model to achieve the above tasks in real-time. |
SHILIN XU et. al. | arxiv-cs.CV | 2024-01-18 |
| 355 | OMG-Seg: Is One Model Good Enough For All Segmentation? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we address various segmentation tasks, each traditionally tackled by distinct or partially unified models. |
XIANGTAI LI et. al. | arxiv-cs.CV | 2024-01-18 |
| 356 | Uncertainty Estimates for Semantic Segmentation: Providing Enhanced Reliability for Automated Motor Claims Handling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the use of a meta-classification model to empirically assess the precision of segments predicted by a model trained for the semantic segmentation of car body parts. |
Jan Küchler; Daniel Kröll; Sebastian Schoenen; Andreas Witte; | arxiv-cs.CV | 2024-01-17 |
| 357 | Semantic Scene Segmentation for Robotics IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the recent advances in deep learning combined with the boost in the computational capacity and the availability of large-scale labeled datasets have led to significant advances in semantic segmentation. In this chapter, we introduce the task of semantic segmentation and present the deep learning techniques that have been proposed to address this task over the years. |
Juana Valeria Hurtado; Abhinav Valada; | arxiv-cs.RO | 2024-01-15 |
| 358 | Learning Segmented 3D Gaussians Via Efficient Feature Unprojection for Zero-shot Neural Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This issue stems primarily from their redundant learnable attributes assigned on individual Gaussians, leading to a lack of robustness against the 3D-inconsistencies in zero-shot generated raw labels. To address this problem, our work, named Compact Segmented 3D Gaussians (CoSegGaussians), proposes the Feature Unprojection and Fusion module as the segmentation field, which utilizes a shallow decoder generalizable for all Gaussians based on high-level features. |
Bin Dou; Tianyu Zhang; Zhaohui Wang; Yongjia Ma; Zejian Yuan; | arxiv-cs.CV | 2024-01-11 |
| 359 | Attention-based Prohibited Item Detection in X-ray Images During Security Checking Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper focuses on the intelligent detection of prohibited items in X‐ray images during the security checking process. An intelligent semantic segmentation model of prohibited … |
Haigang Zhang; Zihao Zhao; Jinfeng Yang; | IET Image Process. | 2024-01-10 |
| 360 | Generic Knowledge Boosted Pretraining for Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning models are essential for scene classification, change detection, land cover segmentation, and other remote sensing (RS) image understanding tasks. Most backbones of … |
Ziyue Huang; Mingming Zhang; Yuan Gong; Qingjie Liu; Yunhong Wang; | IEEE Transactions on Geoscience and Remote Sensing | 2024-01-09 |
| 361 | Interactive Learning System for 3D Semantic Segmentation with Autonomous Mobile Robots Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Service robots operating in unfamiliar environments require capabilities for autonomous object recognition and learning from user interactions. However, present semantic … |
Akinori Kanechika; Lotfi El Hafi; Akira Taniguchi; Y. Hagiwara; T. Taniguchi; | 2024 IEEE/SICE International Symposium on System … | 2024-01-08 |
| 362 | Primitive Geometry Segment Pre-training for 3D Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We thus present the Primitive Geometry Segment Pre-training (PrimGeoSeg) method to enable the learning of 3D semantic features by pre-training segmentation tasks using only primitive geometric objects for 3D medical image segmentation. |
Ryu Tadokoro; Ryosuke Yamada; Kodai Nakashima; Ryo Nakamura; Hirokatsu Kataoka; | arxiv-cs.CV | 2024-01-07 |
| 363 | Systematic Review of Image Segmentation Using Complex Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This review presents various image segmentation methods using complex networks. |
Amin Rezaei; Fatemeh Asadi; | arxiv-cs.CV | 2024-01-05 |
| 364 | FOSSIL: Free Open-Vocabulary Semantic Segmentation Through Synthetic References Retrieval Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unsupervised Open-Vocabulary Semantic Segmentation aims to segment an image into regions referring to an arbitrary set of concepts described by text, without relying on dense … |
Luca Barsellotti; Roberto Amoroso; L. Baraldi; R. Cucchiara; | 2024 IEEE/CVF Winter Conference on Applications of Computer … | 2024-01-03 |
| 365 | Semantic Image Segmentation By Dynamic Discriminative Prototypes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation achieves significant success through large-scale training data. Meanwhile, few-shot semantic segmentation was proposed to segment image regions of novel … |
Kaipeng Zhang; Yoichi Sato; | IEEE Transactions on Multimedia | 2024-01-01 |
| 366 | Prototype Comparison Convolutional Networks for One-Shot Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In few-shot semantic segmentation (FSS), the key challenges are efficiently tuning the interaction between the support set and the query set and distinguishing between context, … |
LINGBO LI et. al. | IEEE Access | 2024-01-01 |
| 367 | Image Semantic Segmentation Approach Based on DeepLabV3 Plus Network with An Attention Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View |
YANYAN LIU et. al. | Eng. Appl. Artif. Intell. | 2024-01-01 |
| 368 | A Stepwise Refining Image-Level Weakly Supervised Semantic Segmentation Method for Detecting Exposed Surface for Buildings (ESB) From Very High-Resolution Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Exposed surface for buildings (ESB), which refers to exposed surfaces with traces of building construction, often leads to urban dust. Accurate ESB detection is important for … |
Xin Huang; Wenrui Wang; Jiayi Li; Leiguang Wang; Xing Xie; | IEEE Transactions on Geoscience and Remote Sensing | 2024-01-01 |
| 369 | Robust 3D Semantic Segmentation Based on Multi-Phase Multi-Modal Fusion for Intelligent Vehicles Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: 3D semantic segmentation is a key technology for intelligent vehicles. Recently, great efforts have been made to achieve accurate and robust 3D semantic segmentation results … |
PEIZHOU NI et. al. | IEEE Transactions on Intelligent Vehicles | 2024-01-01 |
| 370 | End-to-End Instance-Level Human Parsing By Segmenting Persons Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Instance-level human parsing is aimed at separately partitioning the human body into different semantic parts for each individual, which remains a challenging task due to human … |
Zhuang Li; Leilei Cao; Hongbin Wang; Lihong Xu; | IEEE Transactions on Multimedia | 2024-01-01 |
| 371 | Semantic Anything in 3D Gaussians IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: 3D Gaussian Splatting has emerged as an alternative 3D representation of Neural Radiance Fields (NeRFs), bene-fiting from its high-quality rendering results and real-time … |
XU HU et. al. | ArXiv | 2024-01-01 |
| 372 | On Exploring Shape and Semantic Enhancements for RGB-X Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The robustness of scene segmentation can be enhanced with the aid of other modality information, e.g., thermal or/and depth, under poor environmental conditions. In this context, … |
Yuanjian Yang; Caifeng Shan; Fang Zhao; Wenli Liang; Jungong Han; | IEEE Transactions on Intelligent Vehicles | 2024-01-01 |
| 373 | Mutual Dual-Task Generator With Adaptive Attention Fusion for Image Inpainting Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Image segmentation can reveal the semantic structure information in an image, which is helpful guidance information for image inpainting. Notably, it can help mitigate the … |
Yongle Zhang; Yimin Liu; Ruotong Hu; Qiang Wu; Jian Zhang; | IEEE Transactions on Multimedia | 2024-01-01 |
| 374 | Design of Forward-Looking Sonar System for Real-Time Image Segmentation With Light Multiscale Attention Net Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Forward-looking sonar is a commonly used underwater detection device. However, due to the complex underwater environment, small target areas, and blurred features, the detection … |
DONGDONG ZHAO et. al. | IEEE Transactions on Instrumentation and Measurement | 2024-01-01 |
| 375 | Online Continual Domain Adaptation for Semantic Image Segmentation Using Internal Representations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We develop an online UDA algorithm for semantic segmentation of images that improves model generalization on unannotated domains in scenarios where source data access is restricted during adaptation. |
Serban Stan; Mohammad Rostami; | arxiv-cs.CV | 2024-01-01 |
| 376 | Enhanced Visual SLAM for Construction Robots By Efficient Integration of Dynamic Object Segmentation and Scene Semantics Related Papers Related Patents Related Grants Related Venues Related Experts View |
Liu Yang; Hubo Cai; | Adv. Eng. Informatics | 2024-01-01 |
| 377 | Crop Identification of UAV Images Based on An Unsupervised Semantic Segmentation Method Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Crop identification is a fundamental task in remote sensing image interpretation. The rapid development of unmanned aerial vehicle (UAV) has revolutionized the acquisition of … |
Zebing Zhang; Leiguang Wang; Yuncheng Chen; Chen Zheng; | IEEE Geoscience and Remote Sensing Letters | 2024-01-01 |
| 378 | Advancing Data-Efficient Exploitation for Semi-Supervised Remote Sensing Images Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To reduce the dependence of remote sensing (RS) image semantic segmentation models on extensive pixel-level annotated images, this article aims to address the issue of … |
Liang Lv; Lefei Zhang; | IEEE Transactions on Geoscience and Remote Sensing | 2024-01-01 |
| 379 | Boundary-Guided Lightweight Semantic Segmentation With Multi-Scale Semantic Context Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Lightweight semantic segmentation plays an essential role in image signal processing that is beneficial to many multimedia applications, such as self-driving, robotic vision, and … |
QUAN ZHOU et. al. | IEEE Transactions on Multimedia | 2024-01-01 |
| 380 | Object Pose Estimation From RGB-D Images With Affordance-Instance Segmentation Constraint for Semantic Robot Manipulation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Object pose estimation is a crucial task for semantic robot manipulation involving the detection of suitable manipulation regions. Given the diversity of object shapes and scene … |
Zhongli Wang; Guohui Tian; | IEEE Robotics and Automation Letters | 2024-01-01 |
| 381 | DRD-UNet, A UNet-Like Architecture for Multi-Class Breast Cancer Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Staining of histological slides with Hematoxylin and Eosin is widely used in clinical and laboratory settings as these dyes reveal nuclear structures as well as cytoplasm and … |
Mauricio Alberto Ortega-Ruiz; C. Karabağ; Edgar Roman-Rangel; C. Reyes-Aldasoro; | IEEE Access | 2024-01-01 |
| 382 | RSSGLT: Remote Sensing Image Segmentation Network Based on Global–Local Transformer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Remotely captured images possess an immense scale and object appearance variability due to the complex scene. It becomes challenging to capture the underlying attributes in the … |
S. Kumar; Abhishek Kumar; Dong-Gyu Lee; | IEEE Geoscience and Remote Sensing Letters | 2024-01-01 |
| 383 | Dense Dual-Branch Cross Attention Network for Semantic Segmentation of Large-Scale Point Clouds Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation of large-scale point clouds provides foundational knowledge for various geodetic and cartographic applications, including autonomous driving, smart cities, … |
ZIWEI LUO et. al. | IEEE Transactions on Geoscience and Remote Sensing | 2024-01-01 |
| 384 | Importance Biased Traffic Scene Segmentation in Diverse Weather Conditions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Robust semantic segmentation under adverse weather conditions is an open challenge in autonomous driving applications. The main difficulty comes from the uncontrollability of the … |
Yazhou Liu; Ming Wang; P. Lasang; Quansen Sun; | IEEE Transactions on Intelligent Vehicles | 2024-01-01 |
| 385 | Scene-Adaptive 3D Semantic Segmentation Based on Multi-Level Boundary-Semantic-Enhancement for Intelligent Vehicles Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: 3D semantic segmentation is a key technology of scene understanding in the self-driving field, which remains challenging problems. Recent 3D segmentation methods have achieved … |
Peizhou Ni; Xu Li; Dong Kong; Xiaoqing Yin; | IEEE Transactions on Intelligent Vehicles | 2024-01-01 |
| 386 | SonarNet: Hybrid CNN-Transformer-HOG Framework and Multifeature Fusion Mechanism for Forward-Looking Sonar Image Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Forward-looking sonar (FLS) image segmentation plays a significant role in ocean engineering. However, the existing image segmentation algorithms present difficulties in … |
Ju He; Jianfeng Chen; Hu Xu; Yang Yu; | IEEE Transactions on Geoscience and Remote Sensing | 2024-01-01 |
| 387 | Subclassified Loss: Rethinking Data Imbalance From Subclass Perspective for Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation plays a crucial role in enabling intelligent vehicles to perceive and understand their surroundings. However, datasets used for semantic segmentation often … |
SHOUMENG QIU et. al. | IEEE Transactions on Intelligent Vehicles | 2024-01-01 |
| 388 | 1st Place Solution for 5th LSVOS Challenge: Referring Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we integrate strengths of that leading RVOS models to build up an effective paradigm. |
ZHUOYAN LUO et. al. | arxiv-cs.CV | 2023-12-31 |
| 389 | Promoting Segment Anything Model Towards Highly Accurate Dichotomous Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We have high expectations regarding whether SAM, as a foundation model, can be improved towards highly accurate object segmentation, which is known as dichotomous image segmentation (DIS). To address this issue, we propose DIS-SAM, which advances SAM towards DIS with extremely accurate details. |
Xianjie Liu; Keren Fu; Qijun Zhao; | arxiv-cs.CV | 2023-12-30 |
| 390 | LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce LISA++, an update to the existing LISA model, focusing on improving core functionalities while keeping the base architecture intact. |
SENQIAO YANG et. al. | arxiv-cs.CV | 2023-12-28 |
| 391 | An Improved Baseline for Reasoning Segmentation with Large Language Model IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: While LISA effectively bridges the gap between segmentation and large language models to enable reasoning segmentation, it poses certain limitations: unable to distinguish … |
SENQIAO YANG et. al. | ArXiv | 2023-12-28 |
| 392 | Multi-modality Affinity Inference for Weakly Supervised 3D Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, this paper proposes a simple yet effective scene-level weakly supervised point cloud segmentation method with a newly introduced multi-modality point affinity inference module. |
XIAWEI LI et. al. | arxiv-cs.CV | 2023-12-27 |
| 393 | 2D-Guided 3D Gaussian Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In response, this paper introduces a 3D Gaussian segmentation method implemented with 2D segmentation as supervision. |
KUN LAN et. al. | arxiv-cs.CV | 2023-12-26 |
| 394 | UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we end the current fragmented situation and propose UniRef++ to unify the four reference-based object segmentation tasks with a single architecture. |
JIANNAN WU et. al. | arxiv-cs.CV | 2023-12-25 |
| 395 | WildScenes: A Benchmark for 2D and 3D Semantic Segmentation in Large-scale Natural Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose train-val-test splits for standard benchmarks as well as domain adaptation benchmarks and utilize an automated split generation technique to ensure the balance of class label distributions. |
KAVISHA VIDANAPATHIRANA et. al. | arxiv-cs.RO | 2023-12-23 |
| 396 | Variance-insensitive and Target-preserving Mask Refinement for Interactive Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a novel method, Variance-Insensitive and Target-Preserving Mask Refinement to enhance segmentation quality with fewer user inputs. |
CHAOWEI FANG et. al. | arxiv-cs.CV | 2023-12-21 |
| 397 | Weakly Supervised Semantic Segmentation for Driving Scenes Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose solutions for each issue as follows. |
Dongseob Kim; Seungho Lee; Junsuk Choe; Hyunjung Shim; | arxiv-cs.CV | 2023-12-21 |
| 398 | Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we introduce a novel component segmentation model for LA detection that leverages a few labeled samples and unlabeled images sharing logical constraints. |
SOOPIL KIM et. al. | arxiv-cs.CV | 2023-12-21 |
| 399 | BEVSeg2TP: Surround View Camera Bird’s-Eye-View Based Joint Vehicle Segmentation and Ego Vehicle Trajectory Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The proposed method in this paper predicts trajectories by considering perception and trajectory prediction as a unified system. |
Sushil Sharma; Arindam Das; Ganesh Sistu; Mark Halton; Ciarán Eising; | arxiv-cs.CV | 2023-12-20 |
| 400 | MetaSegNet: Metadata-collaborative Vision-Language Representation Learning for Semantic Segmentation of Remote Sensing Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by the success of Vision Transformers and large language models, we propose a novel metadata-collaborative multimodal segmentation network (MetaSegNet) that applies vision-language representation learning for semantic segmentation of remote sensing images. |
LIBO WANG et. al. | arxiv-cs.CV | 2023-12-19 |
| 401 | All for One, and One for All: UrbanSyn Dataset, The Third Musketeer of Synthetic Driving Scenes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce UrbanSyn, a photorealistic dataset acquired through semi-procedurally generated synthetic urban driving scenarios. |
JOSE L. GÓMEZ et. al. | arxiv-cs.CV | 2023-12-19 |
| 402 | SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we explore a principal way to enhance the quality of object masks produced by different segmentation models. |
MENGYU WANG et. al. | arxiv-cs.CV | 2023-12-19 |
| 403 | The Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment: Official Splits and Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this report, we provide detailed dataset statistics (size, class distribution, dataset splits, etc.) and a comprehensive performance benchmark for instance segmentation, object detection, and CVS prediction. |
ADITYA MURALI et. al. | arxiv-cs.CV | 2023-12-19 |
| 404 | Semantic-Aware Autoregressive Image Modeling for Visual Representation Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This is mainly caused by the challenge that images are not sequential signals and lack a natural order when applying autoregressive modeling. In this study, inspired by human beings’ way of grasping an image, i.e., focusing on the main object first, we present a semantic-aware autoregressive image modeling (SemAIM) method to tackle this challenge. |
Kaiyou Song; Shan Zhang; Tong Wang; | arxiv-cs.CV | 2023-12-16 |
| 405 | SeeThruFinger: See and Grasp Anything with A Multi-Modal Soft Touch Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present SeeThruFinger, a Vision-Based Tactile Sensing (VBTS) architecture using a markerless See-Thru-Network. |
Fang Wan; Zheng Wang; Wei Zhang; Chaoyang Song; | arxiv-cs.RO | 2023-12-15 |
| 406 | Offshore Wind Plant Instance Segmentation Using Sentinel-1 Time Series, GIS, and Semantic Segmentation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study’s primary objective is to detect offshore wind plants at an instance level using semantic segmentation models and Sentinel-1 time series. |
Osmar Luiz Ferreira de Carvalho; Osmar Abilio de Carvalho Junior; Anesmar Olino de Albuquerque; Daniel Guerreiro e Silva; | arxiv-cs.CV | 2023-12-14 |
| 407 | WeatherProof: A Paired-Dataset Approach to Semantic Segmentation in Adverse Weather Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find that training on these paired clear and adverse weather frames which share an underlying scene results in improved performance on adverse weather data. With this knowledge, we propose a training pipeline which accentuates the advantages of paired-data training using consistency losses and language guidance, which leads to performance improvements by up to 18.4% as compared to standard training procedures. |
BLAKE GELLA et. al. | arxiv-cs.CV | 2023-12-14 |
| 408 | Progressive Feature Self-reinforcement for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We further assume that the unmasked confident regions should be robust enough to preserve the global semantics. Building upon this, we introduce a complementary self-enhancement method that constrains the semantic consistency between these confident regions and an augmented image with the same class labels. |
JINGXUAN HE et. al. | arxiv-cs.CV | 2023-12-14 |
| 409 | Semi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This can be because it originally stems from the image classification task and lacks specialized mechanisms to capture fine-grained local semantics that prioritizes in dense prediction. To address this issue, we propose a novel framework called \texttt{MaskMatch}, which enables fine-grained locality learning to achieve better dense segmentation. |
WENTAO PAN et. al. | arxiv-cs.CV | 2023-12-13 |
| 410 | X4D-SceneFormer: Enhanced Scene Understanding on 4D Point Cloud Videos Through Cross-modal Knowledge Transfer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Moreover, the irregularity of point cloud poses a difficulty in aligning temporal information within video sequences. To address these issues, we propose a novel cross-modal knowledge transfer framework, called X4D-SceneFormer. |
LINGLIN JING et. al. | arxiv-cs.CV | 2023-12-12 |
| 411 | Transferring CLIP’s Knowledge Into Zero-Shot Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we focus on zero-shot point cloud semantic segmentation and propose a simple yet effective baseline to transfer the visual-linguistic knowledge implied in CLIP to point cloud encoder at both feature and output levels. |
YUANBIN WANG et. al. | arxiv-cs.CV | 2023-12-12 |
| 412 | Cataract-1K: Cataract Surgery Dataset for Scene Segmentation, Phase Recognition, and Irregularity Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Particularly, surgical scene understanding and phase recognition stand as pivotal pillars within the realm of computer-assisted surgery and post-operative assessment of cataract surgery videos. In this context, we present the largest cataract surgery video dataset that addresses diverse requisites for constructing computerized surgical workflow analysis and detecting post-operative irregularities in cataract surgery. |
NEGIN GHAMSARIAN et. al. | arxiv-cs.CV | 2023-12-11 |
| 413 | Densify Your Labels: Unsupervised Clustering with Bipartite Matching for Weakly Supervised Point Cloud Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a weakly supervised semantic segmentation method for point clouds that predicts per-point labels from just whole-scene annotations while achieving the performance of recent fully supervised approaches. |
SHAOBO XIA et. al. | arxiv-cs.CV | 2023-12-11 |
| 414 | Loss Functions in The Era of Semantic Segmentation: A Survey and Outlook Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To aid researchers in identifying the optimal loss function for their particular application, this survey provides a comprehensive and unified review of $25$ loss functions utilized in image segmentation. |
REZA AZAD et. al. | arxiv-cs.CV | 2023-12-08 |
| 415 | GcDLSeg: Integrating Graph-cut Into Deep Learning for Binary Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To combine the strengths of both approaches, we propose in this study to integrate the graph-cut approach into a deep learning network for end-to-end learning. |
Hui Xie; Weiyu Xu; Ya Xing Wang; John Buatti; Xiaodong Wu; | arxiv-cs.CV | 2023-12-07 |
| 416 | Auto-Vocabulary Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce \textit{Auto-Vocabulary Semantic Segmentation (AVS)}, advancing open-ended image understanding by eliminating the necessity to predefine object categories for segmentation. |
Osman Ülger; Maksymilian Kulicki; Yuki Asano; Martin R. Oswald; | arxiv-cs.CV | 2023-12-07 |
| 417 | Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing methods heavily rely on data augmentation and memory buffer, which entail high computational resource demands when applying them to handle semantic segmentation that requires to preserve high-resolution feature maps for making dense pixel-wise predictions. In order to address this problem, we present Augmentation-free Dense Contrastive Knowledge Distillation (Af-DCD), a new contrastive distillation learning paradigm to train compact and accurate deep neural networks for semantic segmentation applications. |
Jiawei Fan; Chao Li; Xiaolong Liu; Meina Song; Anbang Yao; | arxiv-cs.CV | 2023-12-07 |
| 418 | DeepPyramid+: Medical Image Segmentation Using Pyramid View Fusion and Deformable Pyramid Reception Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a network architecture, DeepPyramid+, which addresses diverse challenges encountered in medical image and surgical video segmentation. |
Negin Ghamsarian; Sebastian Wolf; Martin Zinkernagel; Klaus Schoeffmann; Raphael Sznitman; | arxiv-cs.CV | 2023-12-06 |
| 419 | Novel Class Discovery Meets Foundation Models for 3D Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The task of Novel Class Discovery (NCD) in semantic segmentation entails training a model able to accurately segment unlabelled (novel) classes, relying on the available supervision from annotated (base) classes. |
Luigi Riz; Cristiano Saltori; Yiming Wang; Elisa Ricci; Fabio Poiesi; | arxiv-cs.CV | 2023-12-06 |
| 420 | Foundation Model Assisted Weakly Supervised Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a coarse-to-fine framework based on CLIP and SAM for generating high-quality segmentation seeds. |
Xiaobo Yang; Xiaojin Gong; | arxiv-cs.CV | 2023-12-06 |
| 421 | Segment Anything Model (SAM) for Medical Image Segmentation: A Preliminary Review Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Medical image segmentation is a critical component in a variety of clinical applications, facilitating accurate diagnosis and treatment planning. The Segment Anything Model (SAM), … |
Leying Zhang; Xiaokang Deng; Yu Lu; | 2023 IEEE International Conference on Bioinformatics and … | 2023-12-05 |
| 422 | Location-Aware Transformer Network for Few-Shot Medical Image Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic and precise organ segmentation plays a significant role in promoting the development of the diagnosis and treatment of the disease. Despite making enormous strides in … |
Wendong Huang; Bin Xiao; Jinwu Hu; Xiuli Bi; | 2023 IEEE International Conference on Bioinformatics and … | 2023-12-05 |
| 423 | SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a streamlined framework aimed at leveraging the raw output of SAM by exploiting two novel concepts called SAM-Generated Object (SGO) and SAM-Generated Boundary (SGB). |
XIANPING MA et. al. | arxiv-cs.CV | 2023-12-04 |
| 424 | SRSNetwork: Siamese Reconstruction-Segmentation Networks Based on Dynamic-Parameter Convolution Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a high-performance deep neural network for weak target image segmentation, including medical image segmentation and infrared image segmentation. |
BINGKUN NIAN et. al. | arxiv-cs.CV | 2023-12-04 |
| 425 | G2D: From Global to Dense Radiography Representation Learning Via Vision-Language Pre-training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new VLP framework, named \textbf{G}lobal to \textbf{D}ense level representation learning (G2D) that achieves significantly improved granularity and more accurate grounding for the learned features, compared to existing medical VLP approaches. |
CHE LIU et. al. | arxiv-cs.CV | 2023-12-03 |
| 426 | A Review and A Robust Framework of Data-Efficient 3D Scene Parsing with Traditional/Learned 3D Descriptors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents a general and simple framework to tackle point cloud understanding when labels are limited. |
Kangcheng Liu; | arxiv-cs.CV | 2023-12-02 |
| 427 | CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present CellMixer, an innovative annotation-free approach for the semantic segmentation of heterogeneous cell populations. |
MEHDI NAOUAR et. al. | arxiv-cs.CV | 2023-12-01 |
| 428 | Twin-SegNet: Dynamically Coupled Complementary Segmentation Networks for Generalized Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shahed Ahmed; Md. Kamrul Hasan; | Comput. Vis. Image Underst. | 2023-12-01 |
| 429 | Semantic Segmentation in Thermal Videos: A New Benchmark and Multi-Granularity Contrastive Learning-Based Framework Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Video semantic segmentation has achieved great success, which is significant for road scene understanding. However, semantic segmentation remains challenging in poor illumination … |
Yu Zheng; F. Zhou; Shangying Liang; Wentao Song; X. Bai; | IEEE Transactions on Intelligent Transportation Systems | 2023-12-01 |
| 430 | Efficient Multimodal Semantic Segmentation Via Dual-Prompt Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing approaches often fully fine-tune a dual-branch encoder-decoder framework with a complicated feature fusion strategy for achieving multimodal semantic segmentation, which is training-costly due to the massive parameter updates in feature extraction and fusion. To address this issue, we propose a surprisingly simple yet effective dual-prompt learning network (dubbed DPLNet) for training-efficient multimodal (e.g., RGB-D/T) semantic segmentation. |
SHAOHUA DONG et. al. | arxiv-cs.CV | 2023-12-01 |
| 431 | The Impact of Adversarial Attacks on Interpretable Semantic Segmentation in Cyber–Physical Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The widespread adoption of deep learning (DL) models raises concerns about their trustworthiness and reliability. Adversarial attacks are cyber-related attacks that target the DL … |
Rokas Gipiškis; Diletta Chiaro; Marco Preziosi; Edoardo Prezioso; F. Piccialli; | IEEE Systems Journal | 2023-12-01 |
| 432 | 3D Semantic Segmentation of Aerial Photogrammetry Models Based on Orthographic Projection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation of 3D scenes is one of the most important tasks in the field of computer vision and has attracted much attention. In this paper, we propose a novel framework … |
Mengqi Rong; Shuhan Shen; | IEEE Transactions on Circuits and Systems for Video … | 2023-12-01 |
| 433 | Temporal Feature Matching and Propagation for Semantic Segmentation on 3D Point Cloud Sequences Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In real-world LiDAR-based applications, data is generated in the form of 3D point cloud sequences or 4D point clouds. However, the topic of semantic segmentation on 4D point … |
Hanyu Shi; Ruibo Li; Fayao Liu; Guosheng Lin; | IEEE Transactions on Circuits and Systems for Video … | 2023-12-01 |
| 434 | A Lightweight Clustering Framework for Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We thus propose a lightweight clustering framework for unsupervised semantic segmentation. |
Yau Shing Jonathan Cheung; Xi Chen; Lihe Yang; Hengshuang Zhao; | arxiv-cs.CV | 2023-11-30 |
| 435 | SAMPro3D: Locating SAM Prompts in 3D for Zero-Shot Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce SAMPro3D for zero-shot 3D indoor scene segmentation. |
MUTIAN XU et. al. | arxiv-cs.CV | 2023-11-29 |
| 436 | Continual Learning for Image Segmentation with Dynamic Query Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a simple, yet effective Continual Image Segmentation method with incremental Dynamic Query (CISDQ), which decouples the representation learning of both old and new knowledge with lightweight query embedding. |
WEIJIA WU et. al. | arxiv-cs.CV | 2023-11-29 |
| 437 | ALSTER: A Local Spatio-Temporal Expert for Online 3D Semantic Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an online 3D semantic segmentation method that incrementally reconstructs a 3D semantic map from a stream of RGB-D frames. |
SILVAN WEDER et. al. | arxiv-cs.CV | 2023-11-29 |
| 438 | Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To avoid quantized information loss, in this paper, we propose a novel spherical frustum structure. |
Yu Zheng; Guangming Wang; Jiuming Liu; Marc Pollefeys; Hesheng Wang; | arxiv-cs.CV | 2023-11-29 |
| 439 | Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, leveraging the learned association for open-vocabulary semantic segmentation remains a challenge. In this paper, we propose a simple, yet extremely effective, training-free technique, Plug-and-Play Open-Vocabulary Semantic Segmentation (PnP-OVSS) for this task. |
Jiayun Luo; Siddhesh Khandelwal; Leonid Sigal; Boyang Li; | arxiv-cs.CV | 2023-11-28 |
| 440 | ScribbleGen: Generative Data Augmentation Improves Scribble-supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose ScribbleGen, a generative data augmentation method that leverages a ControlNet diffusion model conditioned on semantic scribbles to produce high-quality training data. |
Jacob Schnell; Jieke Wang; Lu Qi; Vincent Tao Hu; Meng Tang; | arxiv-cs.CV | 2023-11-28 |
| 441 | Image Segmentation with Traveling Waves in An Exactly Solvable Recurrent Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that this network generates sophisticated spatiotemporal dynamics that can effectively divide an image into groups according to a scene’s structural characteristics. Using an exact solution of the recurrent network’s dynamics, we present a precise description of the mechanism underlying object segmentation in this network, providing a clear mathematical interpretation of how the network performs this task. |
LUISA H. B. LIBONI et. al. | arxiv-cs.CV | 2023-11-28 |
| 442 | 2D Feature Distillation for Weakly- and Semi-Supervised 3D Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an image-guidance network (IGNet) which builds upon the idea of distilling high level feature information from a domain adapted synthetically trained 2D semantic segmentation network. |
Ozan Unal; Dengxin Dai; Lukas Hoyer; Yigit Baran Can; Luc Van Gool; | arxiv-cs.CV | 2023-11-27 |
| 443 | FALCON: Fairness Learning Via Contrastive Attention Approach to Continual Semantic Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel Fairness Learning via Contrastive Attention Approach to continual learning in semantic scene understanding. |
Thanh-Dat Truong; Utsav Prabhu; Bhiksha Raj; Jackson Cothren; Khoa Luu; | arxiv-cs.CV | 2023-11-27 |
| 444 | Adapter Is All You Need for Tuning Visual Tasks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To find a competitive alternative to full fine-tuning, we propose the Multi-cognitive Visual Adapter (Mona) tuning, a novel adapter-based tuning method. |
Dongshuo Yin; Leiyi Hu; Bin Li; Youqun Zhang; | arxiv-cs.CV | 2023-11-25 |
| 445 | Segment (Almost) Nothing: Prompt-Agnostic Adversarial Attacks on Segmentation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose instead to generate prompt-agnostic adversarial attacks by maximizing the $\ell_2$-distance, in the latent space, between the embedding of the original and perturbed images. |
Francesco Croce; Matthias Hein; | arxiv-cs.CV | 2023-11-24 |
| 446 | Language-guided Few-shot Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an innovative solution to tackle the challenge of few-shot semantic segmentation using only language information, i.e.image-level text labels. |
Jing Wang; Yuang Liu; Qiang Zhou; Fan Wang; | arxiv-cs.CV | 2023-11-23 |
| 447 | SegVol: Universal and Interactive Volumetric Medical Image Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a 3D foundation segmentation model, named SegVol, supporting universal and interactive volumetric medical image segmentation. |
Yuxin Du; Fan Bai; Tiejun Huang; Bo Zhao; | arxiv-cs.CV | 2023-11-22 |
| 448 | Instance-aware 3D Semantic Segmentation Powered By Shape Generators and Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we proposed a novel instance-aware approach for 3D semantic segmentation. |
Bo Sun; Qixing Huang; Xiangru Huang; | arxiv-cs.CV | 2023-11-20 |
| 449 | Generalized Category Discovery in Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a straightforward yet effective framework that reinterprets the GCDSS challenge as a task of mask classification. |
ZHENGYUAN PENG et. al. | arxiv-cs.CV | 2023-11-19 |
| 450 | Optimizing Rgb-d Semantic Segmentation Through Multi-modal Interaction and Pooling Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, in indoor environments, the simple input of RGB and depth images often results in a relatively limited acquisition of semantic and spatial information, leading to suboptimal segmentation outcomes. To address this, we propose the Multi-modal Interaction and Pooling Attention Network (MIPANet), a novel approach designed to harness the interactive synergy between RGB and depth modalities, optimizing the utilization of complementary information. |
Shuai Zhang; Minghong Xie; | arxiv-cs.CV | 2023-11-19 |
| 451 | Self-trained Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The aim of this work is to develop a framework to perform embedding-based self-supervised panoptic segmentation using self-training in a synthetic-to-real domain adaptation problem setting. |
Shourya Verma; | arxiv-cs.CV | 2023-11-17 |
| 452 | Labeling Indoor Scenes with Fusion of Out-of-the-Box Perception Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We aim to develop a cost-effective labeling approach to obtain pseudo-labels for semantic segmentation and object instance detection in indoor environments, with the ultimate goal of facilitating the training of lightweight models for various downstream tasks. |
Yimeng Li; Navid Rajabi; Sulabh Shrestha; Md Alimoor Reza; Jana Kosecka; | arxiv-cs.CV | 2023-11-17 |
| 453 | 3DFusion, A Real-time 3D Object Reconstruction Pipeline Based on Streamed Instance Segmented Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve real-time performance, the paper proposes a method that effectively samples consecutive frames to reduce network load while ensuring reconstruction quality. |
Xi Sun; Derek Jacoby; Yvonne Coady; | arxiv-cs.CV | 2023-11-11 |
| 454 | FDNet: Feature Decoupled Segmentation Network for Tooth CBCT Image Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose FDNet, a Feature Decoupled Segmentation Network, to excel in the face of the variable dental conditions encountered in CBCT scans, such as complex artifacts and indistinct tooth boundaries. |
XIANG FENG et. al. | arxiv-cs.CV | 2023-11-11 |
| 455 | U3DS$^3$: Unsupervised 3D Semantic Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents U3DS$^3$, as a step towards completely unsupervised point cloud segmentation for any holistic 3D scenes. |
Jiaxu Liu; Zhengdi Yu; Toby P. Breckon; Hubert P. H. Shum; | arxiv-cs.CV | 2023-11-10 |
| 456 | Lidar Annotation Is All You Need Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The work described in this paper aims to improve the efficiency of image segmentation using a convolutional neural network in a multi-sensor setup. |
Dinar Sharafutdinov; Stanislav Kuskov; Saian Protasov; Alexey Voropaev; | arxiv-cs.CV | 2023-11-08 |
| 457 | Pelvic Floor MRI Segmentation Based on Semi-supervised Deep Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Insufficient segmentation labels limit the precise segmentation and reconstruction of pelvic floor organs. To address these issues, we propose a semi-supervised framework for pelvic organ segmentation. |
JIANWEI ZUO et. al. | arxiv-cs.CV | 2023-11-06 |
| 458 | PotholeGuard: A Pothole Detection Approach By Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our research presents an innovative point cloud-based pothole segmentation architecture. |
SAHIL NAWALE et. al. | arxiv-cs.CV | 2023-11-05 |
| 459 | ISAR: A Benchmark for Single- and Few-Shot Object Instance Segmentation and Re-Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: So far there is neither a method fulfilling all of these requirements in unison nor a benchmark that could be used to test such a method. Addressing this, we propose ISAR, a benchmark and baseline method for single- and few-shot object Instance Segmentation And Re-identification, in an effort to accelerate the development of algorithms that can robustly detect, segment, and re-identify objects from a single or a few sparse training examples. |
Nicolas Gorlo; Kenneth Blomqvist; Francesco Milano; Roland Siegwart; | arxiv-cs.CV | 2023-11-05 |
| 460 | MemorySeg: Online LiDAR Semantic Segmentation with A Latent Memory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle the challenge of exploiting the information from the past frames to improve the predictions of the current frame in an online fashion. |
Enxu Li; Sergio Casas; Raquel Urtasun; | arxiv-cs.CV | 2023-11-02 |
| 461 | FastICENet: A Real-time and Accurate Semantic Segmentation Model for Aerial Remote Sensing River Ice Image Related Papers Related Patents Related Grants Related Venues Related Experts View |
XIUWEI ZHANG et. al. | Signal Process. | 2023-11-01 |
| 462 | Joint Depth Prediction and Semantic Segmentation with Multi-View SAM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With this work we propose a Multi-View Stereo (MVS) technique for depth prediction that benefits from rich semantic features of the Segment Anything Model (SAM). |
Mykhailo Shvets; Dongxu Zhao; Marc Niethammer; Roni Sengupta; Alexander C. Berg; | arxiv-cs.CV | 2023-10-31 |
| 463 | EffSegmentNet: Efficient Design for Real-time Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper represents the EffSegmentNet, which is a powerful real-time semantic segmentation model. It consists of two segments: (1) A novel MetaFormer-based encoder, termed the … |
Cyun-Bo Wang; Jian-Jiun Ding; | 2023 Asia Pacific Signal and Information Processing … | 2023-10-31 |
| 464 | Train One, Generalize to All: Generalizable Semantic Segmentation from Single-Scene to All Adverse Scenes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unsupervised Domain Adaptation (UDA) for semantic segmentation has received widespread attention for its ability to transfer knowledge from the source to target domains without a … |
ZIYANG GONG et. al. | Proceedings of the 31st ACM International Conference on … | 2023-10-26 |
| 465 | SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we demonstrate that the smoothness prior, asserting that close features in a metric space share the same semantics, can significantly simplify segmentation by casting unsupervised semantic segmentation as an energy minimization problem. Under this paradigm, we propose a novel approach called SmooSeg that harnesses self-supervised learning methods to model the closeness relationships among observations as smoothness signals. |
MENGCHENG LAN et. al. | arxiv-cs.CV | 2023-10-26 |
| 466 | Exploring Dual Representations in Large-Scale Point Clouds: A Simple Weakly Supervised Semantic Segmentation Framework Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Existing work shows that 3D point clouds produce only about a 4% drop in semantic segmentation even at 1% random point annotation, which inspires us to further explore how to … |
JIAMING LIU et. al. | Proceedings of the 31st ACM International Conference on … | 2023-10-26 |
| 467 | 4D-Editor: Interactive Object-level Editing in Dynamic Neural Radiance Fields Via 4D Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper targets interactive object-level editing(e.g., deletion, recoloring, transformation, composition) in dynamic scenes. Recently, some methods aiming for flexible editing … |
Dadong Jiang; Zhihui Ke; Xiaobo Zhou; Xidong Shi; | ArXiv | 2023-10-25 |
| 468 | SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we leverage SAM and existing RS object detection datasets to develop an efficient pipeline for generating a large-scale RS segmentation dataset, dubbed SAMRS. |
DI WANG et. al. | nips | 2023-10-24 |
| 469 | ClusterFomer: Clustering As A Universal Visual Learner Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents ClusterFormer, a universal vision model that is based on the Clustering paradigm with TransFormer. |
JAMES LIANG et. al. | nips | 2023-10-24 |
| 470 | Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose $\texttt{ARCO}$, a semi-supervised contrastive learning (CL) framework with stratified group theory for medical image segmentation. |
CHENYU YOU et. al. | nips | 2023-10-24 |
| 471 | GNeSF: Generalizable Neural Semantic Fields Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing approaches still requires expensive per-scene optimization that prohibits generalization to novel scenes during inference. To circumvent this problem, we introduce a generalizable 3D segmentation framework based on implicit representation. |
Hanlin Chen; Chen Li; Mengqi Guo; Zhiwen Yan; Gim Hee Lee; | arxiv-cs.CV | 2023-10-24 |
| 472 | Uncertainty Estimation for Safety-critical Scene Segmentation Via Fine-grained Reward Maximization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel fine-grained reward maximization (FGRM) framework, to address uncertainty estimation by directly utilizing an uncertainty metric related reward function with a reinforcement learning based model tuning paradigm. |
Hongzheng Yang; Cheng Chen; Yueyao CHEN; Hon Chi Yip; DOU QI; | nips | 2023-10-24 |
| 473 | OV-PARTS: Towards Open-Vocabulary Part Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Furthermore, the large-scale vision and language models, which play a key role in the open vocabulary setting, struggle to recognize parts as effectively as objects. To comprehensively investigate and tackle these challenges, we propose an Open-Vocabulary Part Segmentation (OV-PARTS) benchmark. |
MENG WEI et. al. | nips | 2023-10-24 |
| 474 | Label-efficient Segmentation Via Affinity Propagation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we formulate the affinity modeling task as an affinity propagation process, and consequently propose both local and global pairwise affinity terms to generate accurate soft pseudo labels. |
WENTONG LI et. al. | nips | 2023-10-24 |
| 475 | Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes the Object Style Compensation, where we construct the Object-Level Discrepancy Memory with multiple sets of discrepancy features. |
TINGLIANG FENG et. al. | nips | 2023-10-24 |
| 476 | AIMS: All-Inclusive Multi-Level Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new task, All-Inclusive Multi-Level Segmentation (AIMS), which segments visual regions into three levels: part, entity, and relation (two entities with some semantic relationships). |
LU QI et. al. | nips | 2023-10-24 |
| 477 | Anatomically-aware Uncertainty for Semi-supervised Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work proposes a novel method to estimate segmentation uncertainty by leveraging global information from the segmentation masks. |
Sukesh Adiga V; Jose Dolz; Herve Lombaert; | arxiv-cs.CV | 2023-10-24 |
| 478 | Bridging Semantic Gaps for Language-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Such semantic misalignment circulates in pre-training, leading to inferior zero-shot performance in dense predictions due to insufficient visual concepts captured in textual representations. To close such semantic gap, we propose Concept Curation (CoCu), a pipeline that leverages CLIP to compensate for the missing semantics. |
YUN XING et. al. | nips | 2023-10-24 |
| 479 | Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a novel Fairness Continual Learning approach to the semantic segmentation problem. |
Thanh-Dat Truong; Hoang-Quan Nguyen; Bhiksha Raj; Khoa Luu; | nips | 2023-10-24 |
| 480 | CPSeg: Finer-grained Image Semantic Segmentation Via Chain-of-Thought Language Prompting IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Natural scene analysis and remote sensing imagery offer immense potential for advancements in large-scale language-guided context-aware data utilization. This potential is … |
Lei Li; | 2024 IEEE/CVF Winter Conference on Applications of Computer … | 2023-10-24 |
| 481 | Bridging The Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, their potential to enrich 3D scene representation learning is largely untapped due to the existence of the domain gap. In this work, we propose an innovative methodology called Bridge3D to address this gap by pre-training 3D models using features, semantic masks, and captions sourced from foundation models. |
Zhimin Chen; Bing Li; | nips | 2023-10-24 |
| 482 | Augmentation-free Dense Contrastive Distillation for Efficient Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing methods heavily rely on data augmentation and memory buffer, which entail high computational resource demands when applying them to handle semantic segmentation that requires to preserve high-resolution feature maps for making dense pixel-wise predications. In order to alleviate this problem, we present Augmentation-free Dense Contrastive Knowledge Distillation (Af-DCD), a new contrastive distillation learning paradigm to train compact and accurate deep neural networks for semantic segmentation applications. |
Jiawei Fan; Chao Li; Xiaolong Liu; Meina Song; Anbang Yao; | nips | 2023-10-24 |
| 483 | Segment Everything Everywhere All at Once IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present SEEM, a promotable and interactive model for segmenting everything everywhere all at once in an image. |
XUEYAN ZOU et. al. | nips | 2023-10-24 |
| 484 | Pixel-Level Clustering Network for Unsupervised Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a pixel-level clustering framework for segmenting images into regions without using ground truth annotations. |
Cuong Manh Hoang; Byeongkeun Kang; | arxiv-cs.CV | 2023-10-24 |
| 485 | SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the lack of a global view of video content leads to difficulties in effectively utilizing inter-frame relationships and understanding textual descriptions of object temporal variations. To address this issue, we propose Semantic-assisted Object Cluster (SOC), which aggregates video content and textual guidance for unified temporal modeling and cross-modal alignment. |
ZHUOYAN LUO et. al. | nips | 2023-10-24 |
| 486 | OpenMask3D: Open-Vocabulary 3D Instance Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While such a representation can be directly employed to perform semantic segmentation, existing methods have limitations in their ability to handle object instances. In this work, we address this limitation, and propose OpenMask3D, which is a zero-shot approach for open-vocabulary 3D instance segmentation. |
AYCA TAKMAZ et. al. | nips | 2023-10-24 |
| 487 | Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It remains a challenging task since (1) it is hard to distinguish concealed objects from the background due to the intrinsic similarity and (2) the sparsely-annotated training data only provide weak supervision for model learning. In this paper, we propose a new WSCOS method to address these two challenges. |
CHUNMING HE et. al. | nips | 2023-10-24 |
| 488 | P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a real-time semantic segmentation architecture named Pyramid Pooling Axial Transformer (P2AT). |
Mohammed A. M. Elhassan; Changjun Zhou; Amina Benabid; Abuzar B. M. Adam; | arxiv-cs.CV | 2023-10-23 |
| 489 | RT-YOSO: Revisiting YOSO for Real-time Panoptic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Panoptic segmentation, a crucial computer vision task for scene understanding, simultaneously combines semantic segmentation and instance segmentation to classify pixels and … |
Abdallah Ammar; Mahmoud I. Khalil; Cherif R. Salama; | 2023 5th Novel Intelligent and Leading Emerging Sciences … | 2023-10-21 |
| 490 | Weakly-Supervised Semantic Segmentation with Image-Level Labels: from Traditional Models to Foundation Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The rapid development of deep learning has driven significant progress in the field of image semantic segmentation – a fundamental task in computer vision. Semantic segmentation … |
Zhaozheng Chen; Qianru Sun; | ArXiv | 2023-10-19 |
| 491 | Lidar Panoptic Segmentation and Tracking Without Bells and Whistles Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we re-think this approach and propose a surprisingly simple yet effective detection-centric network for both LPS and tracking. |
ABHINAV AGARWALLA et. al. | arxiv-cs.CV | 2023-10-19 |
| 492 | Minimalist and High-Performance Semantic Segmentation with Plain Vision Transformers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: As a result, we introduce the PlainSeg, a model comprising only three 3$\times$3 convolutions in addition to the transformer layers (either encoder or decoder). |
Yuanduo Hong; Jue Wang; Weichao Sun; Huihui Pan; | arxiv-cs.CV | 2023-10-19 |
| 493 | SegmATRon: Embodied Adaptive Semantic Segmentation for Indoor Environment Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents an adaptive transformer model named SegmATRon for embodied image semantic segmentation. |
Tatiana Zemskova; Margarita Kichik; Dmitry Yudin; Aleksei Staroverov; Aleksandr Panov; | arxiv-cs.CV | 2023-10-18 |
| 494 | Multi Task Consistency Guided Source-Free Test-Time Domain Adaptation Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we introduce a local boundary consistency constraint method that explores the relationship between tissue region segmentation and tissue boundary localization tasks. |
Yanyu Ye; Zhenxi Zhang; Wei Wei; Chunna Tian; | arxiv-cs.CV | 2023-10-18 |
| 495 | Loci-Segmented: Improving Scene Segmentation Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Current slot-oriented approaches for compositional scene segmentation from images and videos rely on provided background information or slot assignments. We present a segmented location and identity tracking system, Loci-Segmented (Loci-s), which does not require either of this information. |
Manuel Traub; Frederic Becker; Adrian Sauter; Sebastian Otte; Martin V. Butz; | arxiv-cs.CV | 2023-10-16 |
| 496 | Volumetric Medical Image Segmentation Via Scribble Annotations and Shape Priors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, most current methods are designed for 2D image segmentation, which do not fully leverage the volumetric information if directly applied to each image slice. In this paper, we propose a scribble-based volumetric image segmentation, Scribble2D5, which tackles 3D anisotropic image segmentation and aims to its improve boundary prediction. |
Qiuhui Chen; Haiying Lyu; Xinyue Hu; Yong Lu; Yi Hong; | arxiv-cs.CV | 2023-10-12 |
| 497 | Detection and Mapping of Chestnut Using Deep Learning from High-Resolution UAV-Based RGB Imagery Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The semantic segmentation method based on high-resolution RGB images obtained by unmanned aerial vehicle (UAV) provides a cost-effective way to improve the accuracy of detection … |
Yifei Sun; Zhenbang Hao; Zhanbao Guo; Zhenhu Liu; Jiaxing Huang; | Remote. Sens. | 2023-10-12 |
| 498 | S4C: Self-Supervised Semantic Scene Completion with Neural Fields IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This process relies on special sensors and annotation by hand which are costly and do not scale well. To overcome this issue, our work presents the first self-supervised approach to SSC called S4C that does not rely on 3D ground truth data. |
Adrian Hayler; Felix Wimbauer; Dominik Muhle; Christian Rupprecht; Daniel Cremers; | arxiv-cs.CV | 2023-10-11 |
| 499 | Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we re-purpose an open-vocabulary detector, segmenter, and dense optical flow estimator, into a model that tracks and segments objects of any category in 2D videos. |
WEN-HSUAN CHU et. al. | arxiv-cs.CV | 2023-10-10 |
| 500 | Densely Connected Swin-UNet for Multiscale Information Aggregation in Medical Image Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Image semantic segmentation is a dense prediction task in computer vision that is dominated by deep learning techniques in recent years. UNet, which is a symmetric encoder-decoder … |
Ziyang Wang; Meiwen Su; Jian-Qing Zheng; Yang Liu; | 2023 IEEE International Conference on Image Processing … | 2023-10-08 |
| 501 | Geometry Aware Field-to-field Transformations for 3D Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel approach to perform 3D semantic segmentation solely from 2D supervision by leveraging Neural Radiance Fields (NeRFs). |
Dominik Hollidt; Clinton Wang; Polina Golland; Marc Pollefeys; | arxiv-cs.CV | 2023-10-08 |
| 502 | Structure-Preserving Instance Segmentation Via Skeleton-Aware Distance Transform Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While the distance transform (DT) makes instance interiors and boundaries more distinguishable, it tends to overlook the intra-object connectivity for instances with varying width and result in over-segmentation. To address these challenges, we propose a skeleton-aware distance transform (SDT) that combines the merits of object skeleton in preserving connectivity and DT in modeling geometric arrangement to represent instances with arbitrary structures. |
ZUDI LIN et. al. | arxiv-cs.CV | 2023-10-08 |
| 503 | Towards Dynamic and Small Objects Refinement for Unsupervised Domain Adaptative Nighttime Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel UDA method that refines both label and feature levels for dynamic and small objects for nighttime semantic segmentation. |
Jingyi Pan; Sihang Li; Yucheng Chen; Jinjing Zhu; Lin Wang; | arxiv-cs.CV | 2023-10-07 |
| 504 | A Deeply Supervised Semantic Segmentation Method Based on GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose an improved semantic segmentation model that combines the strengths of adversarial learning with state-of-the-art semantic segmentation techniques. |
Wei Zhao; Qiyu Wei; Zeng Zeng; | arxiv-cs.CV | 2023-10-06 |
| 505 | DiffPrompter: Differentiable Implicit Visual Prompts for Semantic-Segmentation in Adverse Conditions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce DiffPrompter, a novel differentiable visual and latent prompting mechanism aimed at expanding the learning capabilities of existing adaptors in foundation models. |
SANKET KALWAR et. al. | arxiv-cs.CV | 2023-10-06 |
| 506 | Ablation Study to Clarify The Mechanism of Object Segmentation in Multi-Object Representation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Multi-object representation learning aims to represent complex real-world visual input using the composition of multiple objects. Representation learning methods have often used unsupervised learning to segment an input image into individual objects and encode these objects into each latent vector. |
Takayuki Komatsu; Yoshiyuki Ohmura; Yasuo Kuniyoshi; | arxiv-cs.CV | 2023-10-04 |
| 507 | TransRadar: Adaptive-Directional Transformer for Real-Time Multi-View Radar Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel approach to the semantic segmentation of radar scenes using a multi-input fusion of radar data through a novel architecture and loss functions that are tailored to tackle the drawbacks of radar perception. |
Yahia Dalbah; Jean Lahoud; Hisham Cholakkal; | arxiv-cs.CV | 2023-10-03 |
| 508 | CLIP Is Also A Good Teacher: A New Learning Framework for Inductive Zero-shot Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Consequently, we propose CLIP-ZSS (Zero-shot Semantic Segmentation), a simple but effective training framework that enables any image encoder designed for closed-set segmentation applied in zero-shot and open-vocabulary tasks in testing without combining with VLMs or inserting new modules. |
Jialei Chen; Daisuke Deguchi; Chenkai Zhang; Xu Zheng; Hiroshi Murase; | arxiv-cs.CV | 2023-10-03 |
| 509 | STARS: Zero-shot Sim-to-Real Transfer for Segmentation of Shipwrecks in Sonar Imagery Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we address the problem of sim-to-real transfer for object segmentation when there is no access to real examples of an object of interest during training, i.e. zero-shot sim-to-real transfer for segmentation. |
Advaith Venkatramanan Sethuraman; Katherine A. Skinner; | arxiv-cs.CV | 2023-10-02 |
| 510 | Semantic Motif Segmentation of Archaeological Fresco Fragments Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Archaeological fragment processing is crucial to support the analysis of pictorial contents of broken artifacts. In this paper, we focus on the unexplored task of semantic … |
Aref Enayati; Luca Palmieri; S. Vascon; M. Pelillo; Sinem Aslan; | 2023 IEEE/CVF International Conference on Computer Vision … | 2023-10-02 |
| 511 | Lightweight Semantic Segmentation Network for Semantic Scene Understanding on Low-Compute Devices Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic scene understanding is beneficial for mobile robots. Semantic information obtained through onboard cameras can improve robots’ navigation performance. However, obtaining … |
H. Son; James Weiland; | 2023 IEEE/RSJ International Conference on Intelligent … | 2023-10-01 |
| 512 | Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a simple and efficient topology-aware energy loss function-based network training strategy named EIEGSeg is proposed. |
Yaxin Feng; Yuan Lan; Luchan Zhang; Guoqing Liu; Yang Xiang; | arxiv-cs.CV | 2023-10-01 |
| 513 | CompUDA: Compositional Unsupervised Domain Adaptation for Semantic Segmentation Under Adverse Conditions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In autonomous driving, performing robust semantic segmentation under adverse weather conditions is a long-standing challenge. Imperfect camera observations under adverse … |
Ziqiang Zhengl; Yingshu Chen; Binh-Son Hua; Sai-Kit Yeung; | 2023 IEEE/RSJ International Conference on Intelligent … | 2023-10-01 |
| 514 | TROSD: A New RGB-D Dataset for Transparent and Reflective Object Segmentation in Practice Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Transparent and reflective objects are omnipresent in our daily life, but their unique visual and optical characteristics are notoriously challenging even for state-of-the-art … |
Tianyu Sun; Guodong Zhang; Wenming Yang; Jing-Hao Xue; Guijin Wang; | IEEE Transactions on Circuits and Systems for Video … | 2023-10-01 |
| 515 | Propagating Semantic Labels in Video Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents a method for performing segmentation for objects in video. |
David Balaban; Justin Medich; Pranay Gosar; Justin Hart; | arxiv-cs.CV | 2023-10-01 |
| 516 | Large-scale Apple Orchard Mapping from Multi-source Data Using The Semantic Segmentation Model with Image- To- Image Translation and Transfer Learning Related Papers Related Patents Related Grants Related Venues Related Experts View |
TINGTING ZHANG et. al. | Comput. Electron. Agric. | 2023-10-01 |
| 517 | An Easy Zero-shot Learning Combination: Texture Sensitive Semantic Segmentation IceHrNet and Advanced Style Transfer Learning Strategy Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We proposed an easy method of Zero-Shot semantic segmentation by using style transfer. |
ZHIYONG YANG et. al. | arxiv-cs.CV | 2023-09-30 |
| 518 | Dual-Augmented Transformer Network for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore the dual-augmented transformer network with self-regularization constraints for WSSS. |
Jingliang Deng; Zonghan Li; | arxiv-cs.CV | 2023-09-30 |
| 519 | SegRCDB: Semantic Segmentation Via Formula-Driven Supervised Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the Segmentation Radial Contour DataBase (SegRCDB), which for the first time applies formula-driven supervised learning for semantic segmentation. |
RISA SHINODA et. al. | arxiv-cs.CV | 2023-09-29 |
| 520 | Voting Network for Contour Levee Farmland Segmentation and Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present an end-to-end trainable network for segmenting farmlands with contour levees from high-resolution aerial imagery. |
Abolfazl Meyarian; Xiaohui Yuan; | arxiv-cs.CV | 2023-09-28 |
| 521 | Model2Scene: Learning 3D Scene Representation Via Contrastive Language-CAD Models Pre-training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Model2Scene, a novel paradigm that learns free 3D scene representation from Computer-Aided Design (CAD) models and languages. |
RUNNAN CHEN et. al. | arxiv-cs.CV | 2023-09-28 |
| 522 | COMNet: Co-Occurrent Matching for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Co-Occurrent Matching Network (COMNet), which can promote the quality of the CAMs and enforce the network to pay attention to the entire parts of objects. |
Yukun Su; Jingliang Deng; Zonghan Li; | arxiv-cs.CV | 2023-09-28 |
| 523 | Towards Content-based Pixel Retrieval in Revisited Oxford and Paris Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces the first two landmark pixel retrieval benchmarks. |
GUOYUAN AN et. al. | iccv | 2023-09-27 |
| 524 | Exploring Open-Vocabulary Semantic Segmentation from CLIP Vision Encoder Distillation Only IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing approaches often rely on expensive human annotations as supervision for model training, limiting their scalability to large, unlabeled datasets. To address this challenge, we present ZeroSeg, a novel method that leverages the existing pretrained vision-language (VL) model (e.g. CLIP vision encoder) to train open-vocabulary zero-shot semantic segmentation models. |
JUN CHEN et. al. | iccv | 2023-09-27 |
| 525 | Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a continual-learning method to segment object instances from image-level labels. |
YU-HSING HSIEH et. al. | iccv | 2023-09-27 |
| 526 | SATR: Zero-Shot Semantic Segmentation of 3D Shapes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the task of zero-shot semantic segmentation of 3D shapes by using large-scale off-the-shelf 2D im- age recognition models. |
Ahmed Abdelreheem; Ivan Skorokhodov; Maks Ovsjanikov; Peter Wonka; | iccv | 2023-09-27 |
| 527 | SA-BEV: Generating Semantic-Aware Bird’s-Eye-View Feature for Multi-view 3D Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Semantic-Aware BEV Pooling (SA-BEVPool), which can filter out background information according to the semantic segmentation of image features and transform image features into semantic-aware BEV features. |
Jinqing Zhang; Yanan Zhang; Qingjie Liu; Yunhong Wang; | iccv | 2023-09-27 |
| 528 | Unsupervised Video Object Segmentation with Online Adversarial Self-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose to perform online fine-tuning on the pre-trained segmentation model to adapt to any ad-hoc videos at the test time. |
Tiankang Su; Huihui Song; Dong Liu; Bo Liu; Qingshan Liu; | iccv | 2023-09-27 |
| 529 | Coarse-to-Fine Amodal Segmentation with Shape Prior IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Amodal object segmentation is a challenging task that involves segmenting both visible and occluded parts of an object. In this paper, we propose a novel approach, called Coarse-to-Fine Segmentation (C2F-Seg), that addresses this problem by progressively modeling the amodal segmentation. |
JIANXIONG GAO et. al. | iccv | 2023-09-27 |
| 530 | CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a simple yet effective Contextual Point Cloud Modeling (CPCM) method that consists of two parts: a region-wise masking (RegionMask) strategy and a contextual masked training (CMT) method. |
LIZHAO LIU et. al. | iccv | 2023-09-27 |
| 531 | Re:PolyWorld – A Graph Neural Network for Polygonal Scene Parsing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The objective of this work was to overcome weaknesses and shortcomings of the original model, as well as introducing an improved polygonal representation to obtain a general-purpose method for polygon extraction in images. |
Stefano Zorzi; Friedrich Fraundorfer; | iccv | 2023-09-27 |
| 532 | Parametric Depth Based Feature Representation Learning for Object Detection and Segmentation in Bird’s-Eye View Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In contrast, we propose to use parametric depth distribution modeling for feature transformation. |
Jiayu Yang; Enze Xie; Miaomiao Liu; Jose M. Alvarez; | iccv | 2023-09-27 |
| 533 | Stochastic Segmentation with Conditional Categorical Diffusion Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this context, stochastic semantic segmentation methods must learn to predict conditional distributions of labels given the image, but this is challenging due to the typically multimodal distributions, high-dimensional output spaces, and limited annotation data. To address these challenges, we propose a conditional categorical diffusion model (CCDM) for semantic segmentation based on Denoising Diffusion Probabilistic Models. |
LUKAS ZBINDEN et. al. | iccv | 2023-09-27 |
| 534 | CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a novel unsupervised Cross-Modality Domain Adaptation (CMDA) framework to leverage multi-modality (Images and Events) information for nighttime semantic segmentation, with only labels on daytime images. |
RUIHAO XIA et. al. | iccv | 2023-09-27 |
| 535 | Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a weakly supervised learning method for RIS that only uses readily available image-text pairs. |
JUNGBEOM LEE et. al. | iccv | 2023-09-27 |
| 536 | SegGPT: Towards Segmenting Everything in Context IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present SegGPT, a generalist model for segmenting everything in context. |
XINLONG WANG et. al. | iccv | 2023-09-27 |
| 537 | Domain Generalization of 3D Semantic Segmentation in Autonomous Driving IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite its importance, domain generalization is relatively unexplored in the case of 3D autonomous driving semantic segmentation. To fill this gap, this paper presents the first benchmark for this application by testing state-of-the-art methods and discussing the difficulty of tackling Laser Imaging Detection and Ranging (LiDAR) domain shifts. |
Jules Sanchez; Jean-Emmanuel Deschaud; François Goulette; | iccv | 2023-09-27 |
| 538 | Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited Samples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, in more realistic scenarios, only minimal annotations are available for a new scene, which poses significant challenges to existing RVOS methods. With this in mind, we propose a simple yet effective model with a newly designed cross-modal affinity (CMA) module based on a Transformer architecture. |
Guanghui Li; Mingqi Gao; Heng Liu; Xiantong Zhen; Feng Zheng; | iccv | 2023-09-27 |
| 539 | MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To investigate the feasibility of using motion expressions to ground and segment objects in videos, we propose a large-scale dataset called MeViS, which contains numerous motion expressions to indicate target objects in complex environments. |
Henghui Ding; Chang Liu; Shuting He; Xudong Jiang; Chen Change Loy; | iccv | 2023-09-27 |
| 540 | 3D Segmentation of Humans in Point Clouds with Synthetic Data IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Few works have attempted to directly segment humans in cluttered 3D scenes, which is largely due to the lack of annotated training data of humans interacting with 3D scenes. We address this challenge and propose a framework for generating training data of synthetic humans interacting with real 3D scenes. |
AYÇA TAKMAZ et. al. | iccv | 2023-09-27 |
| 541 | Open-vocabulary Object Segmentation with Diffusion Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The goal of this paper is to extract the visual-language correspondence from a pre-trained text-to-image diffusion model, in the form of segmentation map, i.e., simultaneously generating images and segmentation masks for the corresponding visual entities described in the text prompt. |
ZIYI LI et. al. | iccv | 2023-09-27 |
| 542 | MasQCLIP for Open-Vocabulary Universal Image Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a new method for open-vocabulary universal image segmentation, which is capable of performing instance, semantic, and panoptic segmentation under a unified framework. |
Xin Xu; Tianyi Xiong; Zheng Ding; Zhuowen Tu; | iccv | 2023-09-27 |
| 543 | Continual Segment: Towards A Single, Unified and Non-forgetting Continual Segmentation Model of 143 Whole-body Organs in CT Scans IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new architectural CSS learning framework to learn a single deep segmentation model for segmenting a total of 143 whole-body organs. |