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2s-agcn

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19

lightweight-human-pose-estimation.pytorch

Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.

motif-stgcn

ms-g3d

[CVPR 2020 Oral] PyTorch implementation of "Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition"

msst-rt

openpose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

pggan-pytorch

:fire::fire: PyTorch implementation of "Progressive growing of GANs (PGGAN)" :fire::fire:

sgn

This is the implementation of CVPR2020 paper “Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition”.

shift-gcn

The implementation for "Skeleton-Based Action Recognition with Shift Graph Convolutional Network" (CVPR2020 oral).

shift-gcn-plus

The implementation for "Extremely Lightweight Skeleton-Based Action Recognition with ShiftGCN++." (TIP 2021).

st-gcn

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch