https://github.com/github-zbx/ST-GCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
Papers with Code 아카이브
Multimodal Activity Recognition
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/google-research/google-research/tree/master/assemblenet
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures
https://github.com/hariharannatesh/Action-Recognition-using-Pytorch-Geometric
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/iamhoushiyou/tsn
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/ken724049/action-recognition
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/kennymckormick/pyskl
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/l13025816/PGCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/metalbubble/moments_models
Moments in Time Dataset: one million videos for event understanding
https://github.com/metrics-lab/st-fmri
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/mindspore-ai/models/tree/master/research/cv/tsn
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/mtlouie-unm/alome-tsn
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/nhannguyen2709/video_recognition
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/nntanaka/Fourier-Analysis-for-Skeleton-based-Action-Recognition
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/open-mmlab/mmaction2
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/open-mmlab/mmskeleton
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/raphaelmemmesheimer/gimme_signals_action_recognition
Gimme Signals: Discriminative signal encoding for multimodal activity recognition
https://github.com/rijuldhir/TSM
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/rort1989/HDM
https://github.com/shubhambitsg/activity-recognition
Moments in Time Dataset: one million videos for event understanding
https://github.com/stillarrow/S2VT_ACT
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/sunutf/TSM
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/thefonseca/predictive-coding
Moments in Time Dataset: one million videos for event understanding
https://github.com/wanglichenxj/EV-Action-Electromyography-Vision-Multi-Modal-Action-Dataset
EV-Action: Electromyography-Vision Multi-Modal Action Dataset
https://github.com/zhoubolei/moments_models
Moments in Time Dataset: one million videos for event understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.