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/JoelLeupp/Conv3D-Shot-Boundary-Detection
Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks
https://github.com/JunLi-Galios/CDFL
Weakly Supervised Energy-Based Learning for Action Segmentation
https://github.com/LiwenWang919/M3-UDA
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation
https://github.com/MS-Mind/MS-Code-06/tree/main/OSVOS
https://github.com/MikeG112/RFSBD
Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks
https://github.com/Mind23-2/MindCode-5/tree/main/OSVOS
https://github.com/MindCode-4/code-4/tree/main/sam
https://github.com/MindSpore-scientific/code-7/tree/main/SAM
https://github.com/SamvitJ/Accel
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video
https://github.com/SilvioGiancola/SoccerNetv2-DevKit
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
https://github.com/StanLei52/GEBD
Generic Event Boundary Detection: A Benchmark for Event Segmentation
https://github.com/T-a-g-z/Yotube-VOS-OVS
https://github.com/Tangshitao/ClipShots_basline
Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks
https://github.com/TripleJoy/SAM2MOT
https://github.com/VisualAnalysisOfHumans/LOVEU_TRACK1_TOP3_SUBMISSION
Generic Event Boundary Detection: A Benchmark for Event Segmentation
https://github.com/Xiaoqi-Zhao-DLUT/GateNet-RGB-Saliency
https://github.com/abramjos/Scene-boundary-detection
Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks
https://github.com/aimagelab/rmsnet_soccer
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
https://github.com/alibaba/EasyCV
https://github.com/alokssingh/Temporal-segmentation-Shot-boundary
https://github.com/birdman9390/MetaMaskTrack
https://github.com/caolele/caolele.github.io
Analyzing Linear Dynamical Systems: From Modeling to Coding and Learning
https://github.com/code-implementation1/Code6/tree/main/OSVOS
https://github.com/cufctl/segmentation
https://github.com/cvlab-kaist/MUG-VOS
https://github.com/dcnieho/segment-anything-2
https://github.com/dipika-singhania/multi-scale-action-banks
Temporal Aggregate Representations for Long-Range Video Understanding
https://github.com/dxli94/WLASL
TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
https://github.com/emsalinha/videosum-eval
https://github.com/facebookresearch/segment-anything
https://github.com/huggingface/transformers
https://github.com/ibaiGorordo/ONNX-SAM2-Segment-Anything
https://github.com/idea-research/grounded-sam-2
https://github.com/irfanICMLL/ETC-Real-time-Per-frame-Semantic-video-segmentation
Efficient Semantic Video Segmentation with Per-frame Inference
https://github.com/justld/CCNet_paddle
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.