Papers with Code 아카이브

Action Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 15
평가표: 56
보존된 평가 기록: 650

Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.

In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.

Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/YanWei123/PointNet-encoder-and-FoldingNet-decoder-add-quantization-change-latent-code-size-from-512-to-1024

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/YanWei123/Pointnet_encoder_Foldingnet_decoder_quantization

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/YanWei123/Pytorch-implementation-of-FoldingNet-encoder-and-decoder-with-graph-pooling-covariance-add-quanti

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/ZeinabRahbar/Implementation-for-the-paper-of-SEMI-SUPERVISED-CLASSIFICATION-WITH-GRAPH-CONVOLUTIONAL-NETWORKS

Semi-Supervised Classification with Graph Convolutional Networks

Action Recognition

코드

https://github.com/WonJunPark/Efficientnet

https://github.com/WoominM/DeGCN_pytorch

https://github.com/Wuxiao85/paddle_EfficientGCNv

https://github.com/Xiehuaiqi/3D-ResNets-PyTorch-master

https://github.com/XinyuSun/M3Video

https://github.com/XinzeWu/st-GCN

https://github.com/XuHao9166/TSN_BehaviorRecognition_ForwardCalculation

https://github.com/XuHao9166/TSN_BehaviorRecognition_GenerateTrainImages

https://github.com/YanWei123/PointNet-encoder-and-FoldingNet-decoder-add-quantization-change-latent-code-size-from-512-to-1024

https://github.com/YanWei123/Pointnet_encoder_Foldingnet_decoder_quantization

https://github.com/YanWei123/Pytorch-implementation-of-FoldingNet-encoder-and-decoder-with-graph-pooling-covariance-add-quanti

https://github.com/Yang2446/pointnet

https://github.com/YashNita/Separate-Object-Sounds-by-Watching-Unlabeled-Video-PyTorch-

https://github.com/Yindong-Zhang/myGAT

https://github.com/YiruS/pointnet_adversarial

https://github.com/Yonder-OSS/D3M-Primitives

https://github.com/Young98CN/pointconv_pytorch

https://github.com/Ysp9714/SlowFastNet-keras

https://github.com/YunseobShin/wiki_GAT

https://github.com/YutingLi0606/SURE

https://github.com/Yuto0107/pointnet

https://github.com/YvanG/VQGAN-CLIP

https://github.com/ZJCV/Non-local

https://github.com/ZJCV/TSN

https://github.com/ZJUT-ERCISS/c3d_mindspore

https://github.com/ZJUT-ERCISS/zjut_mindvideo/blob/master/msvideo/models/i3d.py

https://github.com/ZJUT-ERCISS/zjut_mindvideo/blob/master/msvideo/models/r2plus1d.py

https://github.com/ZackPashkin/YOLOv3-EfficientNet-EffYolo

https://github.com/ZackPashkin/text2cartoon-pytorch-CLIP

https://github.com/ZeinabRahbar/Implementation-for-the-paper-of-SEMI-SUPERVISED-CLASSIFICATION-WITH-GRAPH-CONVOLUTIONAL-NETWORKS

https://github.com/Zengxianxian727/TPN_paddle

https://github.com/ZhangNYG/BSN

https://github.com/ZhangNYG/ST-GCN

https://github.com/ZhiHanZ/IRIS0-SPAN

https://github.com/ZhihaoZhu/PointNet-Implementation-Tensorflow

https://github.com/Ziyang412/VideoTree