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Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19
🧑🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
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GNN
Skeleton-based Action Recognition
Video datasets
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计算机自学指南
deep learning for image processing including classification and object-detection etc.
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
[ICCV 2023] Official PyTorch implementation of "Rethinking Mobile Block for Efficient Attention-based Models"
Download scripts for EPIC-KITCHENS
Fine grained activity recognition in videos
Our official implementation of "Graph-Based Motion Prediction for Abnormal Action Detection"
[CVPR 2020 Oral] PyTorch implementation of "Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition"
This is the official implemntation for "Multi-scale spatial temporal graph convolutional network for skeleton-based action recognition" AAAI-2021
Info and sample codes for "NTU RGB+D Action Recognition Dataset"
A toolbox for skeleton-based action recognition.
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Sample Fusion Network: An End-to-End Data Augmentation Network for Skeleton-based Human Action Recognition
This is the implementation of CVPR2020 paper “Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition”.
Code for: "Skeleton-Graph: Long-Term 3D Motion Prediction From 2D Observations Using Deep Spatio-Temporal Graph CNNs", ICCV2021 Workshops
ST-GCN-5-25
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