Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
UW-VOS: A Large-Scale Dataset for Underwater Video Object Segmentation
Underwater Video Object Segmentation (VOS) is essential for marine exploration, yet open-air methods suffer significant degradation due to color distortion, low contrast, and prevalent camouflage. A primary hurdle is the…
Video Object SegmentationM2P: Improving Visual Foundation Models with Mask-to-Point Weakly-Supervised Learning for Dense Point Tracking
Tracking Any Point (TAP) has emerged as a fundamental tool for video understanding. Current approaches adapt Vision Foundation Models (VFMs) like DINOv2 via offline finetuning or test-time optimization. However, these VF…
Video Object SegmentationRepresentation LearningPoint TrackingTraining-Free Spatio-temporal Decoupled Reasoning Video Segmentation with Adaptive Object Memory
Reasoning Video Object Segmentation (ReasonVOS) is a challenging task that requires stable object segmentation across video sequences using implicit and complex textual inputs. Previous methods fine-tune Multimodal Large…
Video Object SegmentationVideo SegmentationEfficient-SAM2: Accelerating SAM2 with Object-Aware Visual Encoding and Memory Retrieval
Segment Anything Model 2 (SAM2) shows excellent performance in video object segmentation tasks; however, the heavy computational burden hinders its application in real-time video processing. Although there have been effo…
Video Object SegmentationSeg-ReSearch: Segmentation with Interleaved Reasoning and External Search
Segmentation based on language has been a popular topic in computer vision. While recent advances in multimodal large language models (MLLMs) have endowed segmentation systems with reasoning capabilities, these efforts r…
Video Object Segmentation3AM: 3egment Anything with Geometric Consistency in Videos
Video object segmentation methods like SAM2 achieve strong performance through memory-based architectures but struggle under large viewpoint changes due to reliance on appearance features. Traditional 3D instance segment…
Video Object Segmentation3D Instance SegmentationFew-Shot Video Object Segmentation in X-Ray Angiography Using Local Matching and Spatio-Temporal Consistency Loss
We introduce a novel FSVOS model that employs a local matching strategy to restrict the search space to the most relevant neighboring pixels. Rather than relying on inefficient standard im2col-like implementations (e.g.,…
Video Object SegmentationContrastive LearningVideo SegmentationFast SAM2 with Text-Driven Token Pruning
Segment Anything Model 2 (SAM2), a vision foundation model has significantly advanced in prompt-driven video object segmentation, yet their practical deployment remains limited by the high computational and memory cost o…
Video Object SegmentationVideo SegmentationReMeDI: Refined Memory for Disambiguation of Identities with SAM3 in Surgical Segmentation
Accurate surgical instrument segmentation in endoscopy is crucial for computer-assisted interventions, yet remains challenging due to frequent occlusions, rapid motion, and long-term instrument re-entry. While SAM3 provi…
Video Object SegmentationMotion4D: Learning 3D-Consistent Motion and Semantics for 4D Scene Understanding
Recent advancements in foundation models for 2D vision have substantially improved the analysis of dynamic scenes from monocular videos. However, despite their strong generalization capabilities, these models often lack …
Video Object SegmentationNovel View SynthesisScene UnderstandingReVSeg: Incentivizing the Reasoning Chain for Video Segmentation with Reinforcement Learning
Reasoning-centric video object segmentation is an inherently complex task: the query often refers to dynamics, causality, and temporal interactions, rather than static appearances. Yet existing solutions generally collap…
Video Object SegmentationReinforcement LearningVideo SegmentationEvaluating SAM2 for Video Semantic Segmentation
The Segmentation Anything Model 2 (SAM2) has proven to be a powerful foundation model for promptable visual object segmentation in both images and videos, capable of storing object-aware memories and transferring them te…
Video Semantic SegmentationVideo Object SegmentationHanDyVQA: A Video QA Benchmark for Fine-Grained Hand-Object Interaction Dynamics
Hand-object interaction (HOI) inherently involves dynamics where human manipulations produce distinct spatio-temporal effects on objects. However, existing semantic HOI benchmarks focused either on manipulation or on the…
Video Object SegmentationImage Diffusion Models Exhibit Emergent Temporal Propagation in Videos
Image diffusion models, though originally developed for image generation, implicitly capture rich semantic structures that enable various recognition and localization tasks beyond synthesis. In this work, we investigate …
Video Object SegmentationImage GenerationObject TrackingVideoSeg-R1:Reasoning Video Object Segmentation via Reinforcement Learning
Traditional video reasoning segmentation methods rely on supervised fine-tuning, which limits generalization to out-of-distribution scenarios and lacks explicit reasoning. To address this, we propose \textbf{VideoSeg-R1}…
Video Object SegmentationReinforcement LearningImage SegmentationFlowFeat: Pixel-Dense Embedding of Motion Profiles
Dense and versatile image representations underpin the success of virtually all computer vision applications. However, state-of-the-art networks, such as transformers, produce low-resolution feature grids, which are subo…
Monocular Depth EstimationVideo Object SegmentationSemantic SegmentationLSVOS 2025 Challenge Report: Recent Advances in Complex Video Object Segmentation
This report presents an overview of the 7th Large-scale Video Object Segmentation (LSVOS) Challenge held in conjunction with ICCV 2025. Besides the two traditional tracks of LSVOS that jointly target robustness in realis…
Video Object SegmentationVideo SegmentationRobust Ego-Exo Correspondence with Long-Term Memory
Establishing object-level correspondence between egocentric and exocentric views is essential for intelligent assistants to deliver precise and intuitive visual guidance. However, this task faces numerous challenges, inc…
Video Object SegmentationSAM2-3dMed: Empowering SAM2 for 3D Medical Image Segmentation
Accurate segmentation of 3D medical images is critical for clinical applications like disease assessment and treatment planning. While the Segment Anything Model 2 (SAM2) has shown remarkable success in video object segm…
Medical Image SegmentationVideo Object SegmentationBoundary DetectionWhen Tracking Fails: Analyzing Failure Modes of SAM2 for Point-Based Tracking in Surgical Videos
Video object segmentation (VOS) models such as SAM2 offer promising zero-shot tracking capabilities for surgical videos using minimal user input. Among the available input types, point-based tracking offers an efficient …
Video Object Segmentation