/AS-CAL

Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition

Primary LanguagePythonMIT LicenseMIT

AS-CAL

Introduction

This is the official implementation of "Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition".

Requirements

  • Python 3.6
  • Pytorch 1.0.1

Datasets

  • NTU RGB+D 60:
    Download raw data from https://github.com/shahroudy/NTURGB-D
    Use st-gcn/tools/ntu_gendata.py in https://github.com/yysijie/st-gcn to prepare data
  • NTU RGB+D 120:
    Same as NTU RGB+D 60 but needs some modification for NTU RGB+D 120.
  • SBU, UWA3D, N-UCLA
    Unzip the .zip file in /data and put them into the directory corresponding to the one in codes.

Usage

  • pretrain and then linear evaluation:
    python pretrain_and_linEval.py

  • reload pre-trained models and linear evaluation:
    python linEval.py --mode eval --model_path ./pretrained_model.pth

  • supervised:
    python linEval.py --mode supervise

  • reload pre-trained models and semi-supervised:
    python linEval.py --mode semi --model_path ./pretrained_model.pth

For more customized parameter settings, you can change them in parse_option() and/or parse_option_lin_eval()

License

AS-CAL is released under the MIT License.