DecoupleGCN-DropGraph

The implementation for "Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition" (ECCV2020). The proposed method boosts the performance of spatial-temporal graph convolutional network with NO extra FLOPs, NO extra latency, and NO extra GPU memory cost.

Prerequisite

• PyTorch 0.4.1
• Cuda 9.0

Data Preparation

• Download the raw data of NTU-RGBD and NTU-RGBD120. Put NTU-RGBD data under the directory ./data/nturgbd_raw. Put NTU-RGBD120 data under the directory ./data/nturgbd120_raw.

• For NTU-RGBD, preprocess data with python data_gen/ntu_gendata.py. For NTU-RGBD120, preprocess data with python data_gen/ntu120_gendata.py.

• Generate the bone data with python data_gen/gen_bone_data.py.

• Generate the motion data with python data_gen/gen_motion_data.py.

Training & Testing

• NTU X-view

  python main.py --config ./config/nturgbd-cross-view/train_joint.yaml

  python main.py --config ./config/nturgbd-cross-view/train_bone.yaml

  python main.py --config ./config/nturgbd-cross-view/train_joint_motion.yaml

  python main.py --config ./config/nturgbd-cross-view/train_bone_motion.yaml

• NTU X-sub

  python main.py --config ./config/nturgbd-cross-subject/train_joint.yaml

  python main.py --config ./config/nturgbd-cross-subject/train_bone.yaml

  python main.py --config ./config/nturgbd-cross-subject/train_joint_motion.yaml

  python main.py --config ./config/nturgbd-cross-subject/train_bone_motion.yaml

• For NTU120, change the dataset path in config files, and change num_class in config files from 60 to 120.

Multi-stream ensemble

To ensemble the results of 4 streams. Change models name in ensemble.py depending on your experiment setting. Then run python ensemble.py.

Trained models

We release several trained models:

Citation

If you find this model useful for your resesarch, please use the following BibTeX entry.

@inproceedings{cheng2020eccv,  
  title     = {Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition},  
  author    = {Ke Cheng and Yifan Zhang and Congqi Cao and Lei Shi and Jian Cheng and Hanqing Lu},  
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},  
  year      = {2020},  
}