Papers with Code 아카이브
Video Segmentation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
MUVOD: A Novel Multi-view Video Object Segmentation Dataset and A Benchmark for 3D Segmentation
Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder
CogGen: A Learner-Centered Generative AI Architecture for Intelligent Tutoring with Programming Video
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects
Q-SAM2: Accurate Quantization for Segment Anything Model 2
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost
OmniFall: A Unified Staged-to-Wild Benchmark for Human Fall Detection
ThinkVideo: High-Quality Reasoning Video Segmentation with Chain of Thoughts
Unlocking the Power of SAM 2 for Few-Shot Segmentation
FlowCut: Unsupervised Video Instance Segmentation via Temporal Mask Matching
VolE: A Point-cloud Framework for Food 3D Reconstruction and Volume Estimation
TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild
GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation
The 1st Solution for 4th PVUW MeViS Challenge: Unleashing the Potential of Large Multimodal Models for Referring Video Segmentation
MedSAM2: Segment Anything in 3D Medical Images and Videos
Online Reasoning Video Segmentation with Just-in-Time Digital Twins
Comparative Analysis of Image, Video, and Audio Classifiers for Automated News Video Segmentation
CamSAM2: Segment Anything Accurately in Camouflaged Videos
Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning
Leveraging Vision-Language Models for Open-Vocabulary Instance Segmentation and Tracking
SAM2 for Image and Video Segmentation: A Comprehensive Survey
Open-World Skill Discovery from Unsegmented Demonstrations
OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation
Rethinking Few-Shot Medical Image Segmentation by SAM2: A Training-Free Framework with Augmentative Prompting and Dynamic Matching
Parameter-free Video Segmentation for Vision and Language Understanding
BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports
An Analysis of Data Transformation Effects on Segment Anything 2
Deep learning approaches to surgical video segmentation and object detection: A Scoping Review
Pointmap Association and Piecewise-Plane Constraint for Consistent and Compact 3D Gaussian Segmentation Field
Role of the Pretraining and the Adaptation data sizes for low-resource real-time MRI video segmentation
SASVi - Segment Any Surgical Video
Efficient Portrait Matte Creation With Layer Diffusion and Connectivity Priors
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