https://github.com/hy0523/mtnet
공식 코드Learning Motion and Temporal Cues for Unsupervised Video Object Segmentation
Papers with Code 아카이브
Video Semantic Segmentation
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The goal of video semantic segmentation is to assign a predefined class to each pixel in all frames of a video. This requires the model not only to predict accurate segmentation masks but also to ensure that these masks remain temporally consistent across frames. This task has broad applications in areas such as autonomous driving, medical video analysis, and AR/VR.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hydragon516/dpa
공식 코드Dual Prototype Attention for Unsupervised Video Object Segmentation
https://github.com/hydragon516/gsanet
공식 코드Guided Slot Attention for Unsupervised Video Object Segmentation
https://github.com/hzxie/RMNet
공식 코드Efficient Regional Memory Network for Video Object Segmentation
https://github.com/imatge-upc/rvos-mots
공식 코드https://github.com/insomnia94/FTMU
공식 코드Fast Template Matching and Update for Video Object Tracking and Segmentation
https://github.com/isee-laboratory/referdino-plus
공식 코드ReferDINO-Plus: 2nd Solution for 4th PVUW MeViS Challenge at CVPR 2025
https://github.com/jamalilab/sam4em
공식 코드https://github.com/jerryx1110/robust-video-object-segmentation
공식 코드Towards Robust Video Object Segmentation with Adaptive Object Calibration
https://github.com/jerryx1110/rpcmvos
공식 코드Reliable Propagation-Correction Modulation for Video Object Segmentation
https://github.com/jfzhuang/DAVSS
공식 코드Video Semantic Segmentation with Distortion-Aware Feature Correction
https://github.com/jfzhuang/st_memory
공식 코드Video Semantic Segmentation with Inter-Frame Feature Fusion and Inner-Frame Feature Refinement
https://github.com/jhl-det/rgbd_video_sod
공식 코드ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection
https://github.com/jiawen-zhu/hqtrack
공식 코드https://github.com/jiawen-zhu/trackgpt
공식 코드https://github.com/jimmy-dq/dropmae
공식 코드DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks
https://github.com/jinlab-imvr/surgical-sam-2
공식 코드Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning
https://github.com/kagawa588/gvseg
공식 코드https://github.com/kai422/covos
공식 코드Accelerating Video Object Segmentation with Compressed Video
https://github.com/kfan21/eoras
공식 코드https://github.com/kimsekeun/medivista-sam
공식 코드MediViSTA: Medical Video Segmentation via Temporal Fusion SAM Adaptation for Echocardiography
https://github.com/kyusik-cho/cmom
공식 코드Domain Adaptive Video Semantic Segmentation via Cross-Domain Moving Object Mixing
https://github.com/lancasterli/refsam
공식 코드RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation
https://github.com/lanmng/sitvos
공식 코드Siamese Network with Interactive Transformer for Video Object Segmentation
https://github.com/leipingjie/sam2video
공식 코드https://github.com/lemmersj/ground-truth-or-daer
공식 코드Ground-truth or DAER: Selective Re-query of Secondary Information
https://github.com/leonlha/kinematics-afr
공식 코드https://github.com/leonnnop/locater
공식 코드Local-Global Context Aware Transformer for Language-Guided Video Segmentation
https://github.com/limingxing00/rde-vos-cvpr2022
공식 코드https://github.com/linfengyuan1997/losh
공식 코드LoSh: Long-Short Text Joint Prediction Network for Referring Video Object Segmentation
https://github.com/linjieyangsc/video_seg
공식 코드https://github.com/liuziyang123/faminet
공식 코드https://github.com/lmm077/SWEM
공식 코드SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximization
https://github.com/lojzezust/mmsegmentation-macvi
공식 코드LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark
https://github.com/lojzezust/wasr-t
공식 코드https://github.com/longmalongma/desa2va
공식 코드Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.