Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
M^3-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object Segmentation
Intelligent robots need to interact with diverse objects across various environments. The appearance and state of objects frequently undergo complex transformations depending on the object properties, e.g., phase transit…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic Segmentation+2THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation
In this report, we describe our approach to egocentric video object segmentation. Our method combines large-scale visual pretraining from SAM2 with depth-based geometric cues to handle complex scenes and long-term tracki…
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1VideoMolmo: Spatio-Temporal Grounding Meets Pointing
Spatio-temporal localization is vital for precise interactions across diverse domains, from biological research to autonomous navigation and interactive interfaces. Current video-based approaches, while proficient in tra…
Autonomous DrivingAutonomous NavigationCell TrackingReferring Video Object Segmentation+4InterRVOS: Interaction-aware Referring Video Object Segmentation
Referring video object segmentation aims to segment the object in a video corresponding to a given natural language expression. While prior works have explored various referring scenarios, including motion-centric or mul…
8kObjectReferring Video Object SegmentationSemantic Segmentation+3Omni-R1: Reinforcement Learning for Omnimodal Reasoning via Two-System Collaboration
Long-horizon video-audio reasoning and fine-grained pixel understanding impose conflicting requirements on omnimodal models: dense temporal coverage demands many low-resolution frames, whereas precise grounding calls for…
Domain GeneralizationHallucinationReasoning Video Object SegmentationReferring Audio-Visual Segmentation+4ThinkVideo: High-Quality Reasoning Video Segmentation with Chain of Thoughts
Reasoning Video Object Segmentation is a challenging task, which generates a mask sequence from an input video and an implicit, complex text query. Existing works probe into the problem by finetuning Multimodal Large Lan…
Image SegmentationInstance SegmentationObjectReasoning Video Object Segmentation+6Long-RVOS: A Comprehensive Benchmark for Long-term Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims to identify, track and segment the objects in a video based on language descriptions, which has received great attention in recent years. However, existing datasets remain …
Referring Video Object SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationVideo-GPT via Next Clip Diffusion
GPT has shown its remarkable success in natural language processing. However, the language sequence is not sufficient to describe spatial-temporal details in the visual world. Alternatively, the video sequence is good at…
DenoisingImage AnimationPredictionVideo Classification+46D Pose Estimation on Spoons and Hands
Accurate dietary monitoring is essential for promoting healthier eating habits. A key area of research is how people interact and consume food using utensils and hands. By tracking their position and orientation, it is p…
6D Pose EstimationPose EstimationPositionSemantic Segmentation+2Accelerating Volumetric Medical Image Annotation via Short-Long Memory SAM 2
Manual annotation of volumetric medical images, such as magnetic resonance imaging (MRI) and computed tomography (CT), is a labor-intensive and time-consuming process. Recent advancements in foundation models for video o…
Computed Tomography (CT)Semantic SegmentationVideo Object SegmentationVideo Semantic SegmentationMoSAM: Motion-Guided Segment Anything Model with Spatial-Temporal Memory Selection
The recent Segment Anything Model 2 (SAM2) has demonstrated exceptional capabilities in interactive object segmentation for both images and videos. However, as a foundational model on interactive segmentation, SAM2 perfo…
Instance SegmentationInteractive SegmentationObjectObject Tracking+5RGB-D Video Object Segmentation via Enhanced Multi-store Feature Memory
The RGB-Depth (RGB-D) Video Object Segmentation (VOS) aims to integrate the fine-grained texture information of RGB with the spatial geometric clues of depth modality, boosting the performance of segmentation. However, o…
SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationFew-Shot Referring Video Single- and Multi-Object Segmentation via Cross-Modal Affinity with Instance Sequence Matching
Referring video object segmentation (RVOS) aims to segment objects in videos guided by natural language descriptions. We propose FS-RVOS, a Transformer-based model with two key components: a cross-modal affinity module a…
ObjectReferring Video Object SegmentationSegmentationSemantic Segmentation+2DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
Given a single labeled example, in-context segmentation aims to segment corresponding objects. This setting, known as one-shot segmentation in few-shot learning, explores the segmentation model's generalization ability a…
Few-Shot LearningInteractive SegmentationOne-Shot SegmentationScene Understanding+6PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild
This report provides a comprehensive overview of the 4th Pixel-level Video Understanding in the Wild (PVUW) Challenge, held in conjunction with CVPR 2025. It summarizes the challenge outcomes, participating methodologies…
SegmentationSemantic SegmentationVideo Object SegmentationVideo Segmentation+2MASSeg : 2nd Technical Report for 4th PVUW MOSE Track
Complex video object segmentation continues to face significant challenges in small object recognition, occlusion handling, and dynamic scene modeling. This report presents our solution, which ranked second in the MOSE t…
Data AugmentationObjectObject RecognitionOcclusion Handling+4FVOS for MOSE Track of 4th PVUW Challenge: 3rd Place Solution
Video Object Segmentation (VOS) is one of the most fundamental and challenging tasks in computer vision and has a wide range of applications. Most existing methods rely on spatiotemporal memory networks to extract frame-…
SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationMulti-person Physics-based Pose Estimation for Combat Sports
We propose a novel framework for accurate 3D human pose estimation in combat sports using sparse multi-camera setups. Our method integrates robust multi-view 2D pose tracking via a transformer-based top-down approach, em…
3D Human Pose Estimation3D Multi-Person Pose EstimationMulti-Person Pose EstimationPose Estimation+4STSeg-Complex Video Object Segmentation: The 1st Solution for 4th PVUW MOSE Challenge
Segmentation of video objects in complex scenarios is highly challenging, and the MOSE dataset has significantly contributed to the development of this field. This technical report details the STSeg solution proposed by …
Semantic SegmentationVideo Object SegmentationVideo Semantic SegmentationGLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation
This paper proposes a novel framework utilizing multi-modal large language models (MLLMs) for referring video object segmentation (RefVOS). Previous MLLM-based methods commonly struggle with the dilemma between "Ref" and…
Contrastive LearningLanguage ModelingLanguage ModellingLarge Language Model+6