https://github.com/ModelBunker/PointNet-TensorFlow
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Papers with Code 아카이브
Skeleton Based Action Recognition
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Skeleton-based Action Recognition is a computer vision task that involves recognizing human actions from a sequence of 3D skeletal joint data captured from sensors such as Microsoft Kinect, Intel RealSense, and wearable devices. The goal of skeleton-based action recognition is to develop algorithms that can understand and classify human actions from skeleton data, which can be used in various applications such as human-computer interaction, sports analysis, and surveillance.
<span style="color:grey; opacity: 0.6">( Image credit: View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Moon-Xuezha/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/NVIDIA/flownet2-pytorch
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
https://github.com/Negus25/GAT-Mindspore
https://github.com/OanaIgnat/i3d_keras
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/PPPrior/i3d-pytorch
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/PaParaZz1/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/stgcn.md
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/Phimos/Paddle-PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/Powercoder64/TAA-GCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/PumpkinYing/GAT
https://github.com/SBPL-Cruz/perch_pose_sampler
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/SY-Xuan/pointnet_paddle
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/ShadowShadowWong/update-pointnet-work
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/ShobhitMaheshwari/sign-language1
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/SonuDileep/3-D-Object-Detection-using-PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/StanfordVL/RubiksNet
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/StefOe/indrnn-pytorch
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/Subrata11/IoT-based-Real-time-Human-Motion-Recognition-Based-on-Skeletons-
https://github.com/Sun1992/SSTCN-for-SLR
https://github.com/Sunnydreamrain/IndRNN
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/Sy-Zhang/Geometric-Feature-Release
https://github.com/THHHomas/mls
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/TaatiTeam/STARS
STARS: Self-supervised Tuning for 3D Action Recognition in Skeleton Sequences
https://github.com/TaatiTeam/stgcn_parkinsonism_prediction
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/Taeuk-Jang/pointcompletion
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/TobiasLee/Text-Classification
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/Tudouu/stgcn_light_op
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/TyngJiunKuo/deep-learning-project
https://github.com/VaanHUANG/CSCI5210HW1
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/WangYueFt/dgcnn
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/WantingZhao/my_GAT
https://github.com/WoominM/DeGCN_pytorch
https://github.com/Wuxiao85/paddle_EfficientGCNv
Constructing Stronger and Faster Baselines for Skeleton-based Action Recognition
https://github.com/XinzeWu/st-GCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.