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/Dir-b/PointNet

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

https://github.com/DixinFan/st-gcn

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/DuaneNielsen/keypoints

Unsupervised Learning of Object Keypoints for Perception and Control

https://github.com/DylanWusee/pointconv_pytorch

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

https://github.com/ECE685-FinalProject/3D-object-recognition

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

https://github.com/ELKYang/2s-AGCN-paddle

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/EVOKE-LMM/EVOKE

In-Context Editing: Learning Knowledge from Self-Induced Distributions

https://github.com/Ecgbert/Grad_CAM_PLUS_PLUS

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

https://github.com/ElliotHYLee/VisualOdometry3D

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

https://github.com/ElricXin/Skeleton-MixFormer

Tensor Representations for Action Recognition

https://github.com/FelixMQuintana/Deep-Vasp-E

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

https://github.com/Fragjacker/Pointcloud-grad-CAM

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

https://github.com/FrederikSchorr/sign-language

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

https://github.com/GOD-GOD-Autonomous-Vehicle/self-pointnet

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

https://github.com/Gbouna/Action-Recognition-for-Privacy-Preserving-Ambient-Assisted-Living

https://github.com/Gbouna/HT-ConvNet

https://github.com/GeyuanZhang/st-gcn-master

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/GraphSAINT/GraphSAINT

Graph Attention Networks

https://github.com/HamzaGbada/GCN-Numpy

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/Harut0726/my-pointnet-tensorflow

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

https://github.com/HazyResearch/hgcn

Graph Attention Networks

https://github.com/HeapHop30/graph-attention-nets

Graph Attention Networks

https://github.com/HoganZhang/pygcn_python3

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/HollrayChan/gradcam-plus-plus

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

https://github.com/HuCui2022/JPFormer

https://github.com/ISICV/ManTraNet

https://github.com/IllinoisGraphBenchmark/IGB-Datasets

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/InwoongLee/TS-LSTM

https://github.com/Jagyan/ghost_radarpoint_detection

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

https://github.com/Javed002/Object_detection_PointNet

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

https://github.com/JeffCHEN2017/WSSTG

Finding Action Tubes

https://github.com/KaidongLi/tf-3d-alpha

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

https://github.com/Kaimaoge/IGNNK

Graph Attention Networks

https://github.com/KhusDM/PointNetTree

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

https://github.com/KimMeen/GCN

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/KingGugu/I3D

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

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