https://github.com/0liliulei/mask-vos
공식 코드Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation
Papers with Code 아카이브
Video Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/983632847/awesome-multimodal-object-tracking
공식 코드Underwater Camouflaged Object Tracking Meets Vision-Language SAM2
https://github.com/Ali2500/HODOR
공식 코드https://github.com/Ali2500/TarViS
공식 코드TarViS: A Unified Approach for Target-based Video Segmentation
https://github.com/Andreas-Pfeuffer/LSTM-ICNet
공식 코드https://github.com/AngeLouCN/SAM-2_Surgical_Video
공식 코드Zero-Shot Surgical Tool Segmentation in Monocular Video Using Segment Anything Model 2
https://github.com/HCPLab-SYSU/ATEN
공식 코드Adaptive Temporal Encoding Network for Video Instance-level Human Parsing
https://github.com/HeatherJiaZG/SuperGlue-pytorch
공식 코드Physarum Powered Differentiable Linear Programming Layers and Applications
https://github.com/Jyxarthur/OCLR_model
공식 코드Segmenting Moving Objects via an Object-Centric Layered Representation
https://github.com/MECLabTUDA/SASVi
공식 코드https://github.com/MohsenFayyaz89/STFCN
공식 코드https://github.com/PaddlePaddle/PaddleSeg
공식 코드EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle
https://github.com/Scatteredrain/SALI
공식 코드https://github.com/Sixkplus/TapLab
공식 코드TapLab: A Fast Framework for Semantic Video Segmentation Tapping into Compressed-Domain Knowledge
https://github.com/StevenHickson/4D_Segmentation
공식 코드Efficient Hierarchical Graph-Based Segmentation of RGBD Videos
https://github.com/Tangshitao/ClipShots
공식 코드Fast Video Shot Transition Localization with Deep Structured Models
https://github.com/Va6lue/BST-Badminton-Stroke-type-Transformer
공식 코드BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports
https://github.com/ZhilingYan/Biomedical-SAM-2
공식 코드Biomedical SAM 2: Segment Anything in Biomedical Images and Videos
https://github.com/ais-bonn/nimbro_api
공식 코드Leveraging Vision-Language Models for Open-Vocabulary Instance Segmentation and Tracking
https://github.com/ait-assistive-autonomous-systems/hopomop
공식 코드https://github.com/alimohammadiamirhossein/smite
공식 코드https://github.com/amazon-science/polygon-transformer
공식 코드PolyFormer: Referring Image Segmentation as Sequential Polygon Generation
https://github.com/amirbar/stop
공식 코드Stochastic positional embeddings improve masked image modeling
https://github.com/amirrezahmi/video-inpainting-and-voice-cloning
공식 코드https://github.com/andy-cheng/tempura
공식 코드TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action
https://github.com/angeloucn/min_max_similarity
공식 코드https://github.com/aspirinone/catr.github.io
공식 코드CATR: Combinatorial-Dependence Audio-Queried Transformer for Audio-Visual Video Segmentation
https://github.com/beileicui/ms-tfal
공식 코드https://github.com/bo-miao/HTR
공식 코드Temporally Consistent Referring Video Object Segmentation with Hybrid Memory
https://github.com/bowang-lab/medsam
공식 코드Segment Anything in Medical Images and Videos: Benchmark and Deployment
https://github.com/bowang-lab/medsam2
공식 코드https://github.com/carrierlxk/AGNN
공식 코드Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks
https://github.com/chikap421/mseg_vcuq
공식 코드https://github.com/chikap421/videosam
공식 코드VideoSAM: A Large Vision Foundation Model for High-Speed Video Segmentation
https://github.com/cilinyan/VISA
공식 코드VISA: Reasoning Video Object Segmentation via Large Language Models
https://github.com/cilinyan/revos-api
공식 코드VISA: Reasoning Video Object Segmentation via Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.