https://github.com/zzysteve/skeletonx
공식 코드SkeletonX: Data-Efficient Skeleton-based Action Recognition via Cross-sample Feature Aggregation
Papers with Code 아카이브
Temporal Action Localization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 8
- 평가표
- 14
- 보존된 평가 기록
- 125
Temporal Action Localization aims to detect activities in the video stream and output beginning and end timestamps. It is closely related to Temporal Action Proposal Generation.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://gitlab.com/MISLgit/forensic-similarity-for-digital-images
공식 코드https://huggingface.co/datasets/SoftMINER-Group/NicheHazardQA
공식 코드Sowing the Wind, Reaping the Whirlwind: The Impact of Editing Language Models
https://huggingface.co/datasets/SoftMINER-Group/TechHazardQA
공식 코드https://gitee.com/gai-shaoyan/mind3d
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://gitee.com/zhengkeli/zkl-knowedit-rome
https://github.com/1075225782/GCN
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/1zgh/st-gcn
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/2023-MindSpore-1/ms-code-11/tree/main/gcn
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/2023-MindSpore-1/ms-code-17/tree/main/AVA_cifar
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
https://github.com/2023-MindSpore-1/ms-code-17/tree/main/BMN
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
https://github.com/2023-MindSpore-1/ms-code-187
A Closer Look at Spatiotemporal Convolutions for Action Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/flownet2
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/r2plus1d
A Closer Look at Spatiotemporal Convolutions for Action Recognition
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/stgcn
DG-STGCN: Dynamic Spatial-Temporal Modeling for Skeleton-based Action Recognition
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/stnet
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tracktor
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tracktor%2B%2B
https://github.com/2023-MindSpore-1/ms-code-24
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/2023-MindSpore-1/ms-code-35
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-1/ms-code-49
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-1/ms-code-68
A Closer Look at Spatiotemporal Convolutions for Action Recognition
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tracktor%2B%2B
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tsn
https://github.com/2023-MindSpore-4/Code10/tree/main/VGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code10/tree/main/frustum-pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-4/Code10/tree/main/glore_res
https://github.com/2023-MindSpore-4/Code6/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code7/tree/main/stnet
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
https://github.com/2023-MindSpore-4/Code8/tree/main/AVA_cifar
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
https://github.com/2023-MindSpore-4/Code8/tree/main/BMN
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
https://github.com/2023-MindSpore-4/Code8/tree/main/C3D
R-C3D: Region Convolutional 3D Network for Temporal Activity Detection
https://github.com/2023-MindSpore-4/Code9/tree/main/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-4/Code9/tree/main/VGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.