Papers with Code 아카이브

3D Action Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

6

평가표

3

보존된 평가 기록

13

코드

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

https://github.com/vailatuts/SSFG-regularization

Graph Attention Networks

https://github.com/vcowwy/paddle-grad-cam

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

https://github.com/vijayvee/behavior-recognition

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/vijayvee/behavior_recognition

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/vinits5/learning3d

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

https://github.com/wan2000/mc-mot

Graph Attention Networks

https://github.com/weixuan-wang123/ReMaKE

Editing Large Language Models: Problems, Methods, and Opportunities

https://github.com/weiyangfb/PyTorchSparseGAT

Graph Attention Networks

https://github.com/whut2962575697/gat_sementic_segmentation

Graph Attention Networks

https://github.com/witignite/Frustum-PointNet

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

https://github.com/wonderland-dsg/pointnet-grid

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

https://github.com/wuryantoAji/POINTNET

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

https://github.com/wushidonguc/two-stream-action-recognition-keras

UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

https://github.com/xiaoiker/GCN-NAS

Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching

https://github.com/xiuyu0000/new_papers_codes/tree/main/I3D

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/xiuyu0000/vision/blob/main/mindvision/ms3d/models/pointnet2cls.py

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

https://github.com/xiuyu0000/vision/blob/main/mindvision/msvideo/models/i3d.py

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/xurui1217/pointnet.pytorch-master

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

https://github.com/y2kmz/pointnetv2

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

https://github.com/yCobanoglu/infinite-width-gnns

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/yangjun1994/CAGCN

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/yangyucheng000/pointnet

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

https://github.com/yangyucheng000/unipose-mindspore

UniPose: Unified Human Pose Estimation in Single Images and Videos

https://github.com/yanhuchen/quantum-graph-convolutional-network

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/yanx27/Pointnet

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

https://github.com/yanxp/PointNet

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

https://github.com/yaohungt/GSTEG_CVPR_2019

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/ydtydr/hyla

Simplifying Graph Convolutional Networks

https://github.com/ydzhang-stormstout/HAT

Graph Attention Networks

https://github.com/yevgm/deepadv3d

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

https://github.com/yfsong0709/ResGCNv1

Constructing Stronger and Faster Baselines for Skeleton-based Action Recognition

https://github.com/yiskw713/ClassActivationMapping

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

https://github.com/yiskw713/SmoothGradCAMplusplus

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

https://github.com/yiskw713/scorecam

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

https://github.com/ykrmm/sota_gnn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/ytng001/sensemaking

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

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.