Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
The 1st Solution for MOSEv1 Challenge on LSVOS 2025: CGFSeg
Video Object Segmentation (VOS) aims to track and segment specific objects across entire video sequences, yet it remains highly challenging under complex real-world scenarios. The MOSEv1 and LVOS dataset, adopted in the …
Video Object SegmentationVideo Object Segmentation-Aware Audio Generation
Existing multimodal audio generation models often lack precise user control, which limits their applicability in professional Foley workflows. In particular, these models focus on the entire video and do not provide prec…
Video Object SegmentationAudio GenerationEnhancing Video Object Segmentation in TrackRAD Using XMem Memory Network
This paper presents an advanced tumor segmentation framework for real-time MRI-guided radiotherapy, designed for the TrackRAD2025 challenge. Our method leverages the XMem model, a memory-augmented architecture, to segmen…
Video Object SegmentationTumor SegmentationSAMSON: 3rd Place Solution of LSVOS 2025 VOS Challenge
Large-scale Video Object Segmentation (LSVOS) addresses the challenge of accurately tracking and segmenting objects in long video sequences, where difficulties stem from object reappearance, small-scale targets, heavy oc…
Video Object SegmentationSegment-to-Act: Label-Noise-Robust Action-Prompted Video Segmentation Towards Embodied Intelligence
Embodied intelligence relies on accurately segmenting objects actively involved in interactions. Action-based video object segmentation addresses this by linking segmentation with action semantics, but it depends on larg…
Video Object SegmentationVideo SegmentationEnhancing Sa2VA for Referent Video Object Segmentation: 2nd Solution for 7th LSVOS RVOS Track
Referential Video Object Segmentation (RVOS) aims to segment all objects in a video that match a given natural language description, bridging the gap between vision and language understanding. Recent work, such as Sa2VA,…
Video Object SegmentationVideo SegmentationEnriched Feature Representation and Motion Prediction Module for MOSEv2 Track of 7th LSVOS Challenge: 3rd Place Solution
Video object segmentation (VOS) is a challenging task with wide applications such as video editing and autonomous driving. While Cutie provides strong query-based segmentation and SAM2 offers enriched representations via…
Video Object SegmentationAutonomous DrivingPseudo-Label Enhanced Cascaded Framework: 2nd Technical Report for LSVOS 2025 VOS Track
Complex Video Object Segmentation (VOS) presents significant challenges in accurately segmenting objects across frames, especially in the presence of small and similar targets, frequent occlusions, rapid motion, and comp…
Video Object SegmentationVideo SegmentationIMD: A 6-DoF Pose Estimation Benchmark for Industrial Metallic Objects
Object 6DoF (6D) pose estimation is essential for robotic perception, especially in industrial settings. It enables robots to interact with the environment and manipulate objects. However, existing benchmarks on object 6…
Video Object Segmentation6D Pose EstimationPose TrackingFTIO: Frequent Temporally Integrated Objects
Predicting and tracking objects in real-world scenarios is a critical challenge in Video Object Segmentation (VOS) tasks. Unsupervised VOS (UVOS) has the additional challenge of finding an initial segmentation of salient…
Video Object SegmentationTowards Agentic AI for Multimodal-Guided Video Object Segmentation
Referring-based Video Object Segmentation is a multimodal problem that requires producing fine-grained segmentation results guided by external cues. Traditional approaches to this task typically involve training speciali…
Video Object SegmentationMOSEv2: A More Challenging Dataset for Video Object Segmentation in Complex Scenes
Video object segmentation (VOS) aims to segment specified target objects throughout a video. Although state-of-the-art methods have achieved impressive performance (e.g., 90+% J&F) on benchmarks such as DAVIS and YouTube…
Video Object SegmentationVideo Object TrackingTSMS-SAM2: Multi-scale Temporal Sampling Augmentation and Memory-Splitting Pruning for Promptable Video Object Segmentation and Tracking in Surgical Scenarios
Promptable video object segmentation and tracking (VOST) has seen significant advances with the emergence of foundation models like Segment Anything Model 2 (SAM2); however, their application in surgical video analysis r…
Video Object SegmentationSegment Anything for Video: A Comprehensive Review of Video Object Segmentation and Tracking from Past to Future
Video Object Segmentation and Tracking (VOST) presents a complex yet critical challenge in computer vision, requiring robust integration of segmentation and tracking across temporally dynamic frames. Traditional methods …
Video Object SegmentationComputational EfficiencyDomain GeneralizationMOVE: Motion-Guided Few-Shot Video Object Segmentation
This work addresses motion-guided few-shot video object segmentation (FSVOS), which aims to segment dynamic objects in videos based on a few annotated examples with the same motion patterns. Existing FSVOS datasets and m…
Video Object SegmentationHQ-SMem: Video Segmentation and Tracking Using Memory Efficient Object Embedding With Selective Update and Self-Supervised Distillation Feedback
Video Object Segmentation (VOS) is foundational to numerous computer vision applications, including surveillance, autonomous driving, robotics and generative video editing. However, existing VOS models often struggle wit…
Video Object SegmentationAutonomous DrivingVideo SegmentationSeC: Advancing Complex Video Object Segmentation via Progressive Concept Construction
Video Object Segmentation (VOS) is a core task in computer vision, requiring models to track and segment target objects across video frames. Despite notable advances with recent efforts, current techniques still lag behi…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1ProGait: A Multi-Purpose Video Dataset and Benchmark for Transfemoral Prosthesis Users
Prosthetic legs play a pivotal role in clinical rehabilitation, allowing individuals with lower-limb amputations the ability to regain mobility and improve their quality of life. Gait analysis is fundamental for optimizi…
Video Object Segmentation2D Human Pose EstimationMemory-Augmented SAM2 for Training-Free Surgical Video Segmentation
Surgical video segmentation is a critical task in computer-assisted surgery, essential for enhancing surgical quality and patient outcomes. Recently, the Segment Anything Model 2 (SAM2) framework has demonstrated remarka…
SegmentationSemantic SegmentationVideo Object SegmentationVideo Segmentation+1MUVOD: A Novel Multi-view Video Object Segmentation Dataset and A Benchmark for 3D Segmentation
The application of methods based on Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3D GS) have steadily gained popularity in the field of 3D object segmentation in static scenes. These approaches demonstrate ef…
NeRFObjectScene UnderstandingSegmentation+4