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HMGAN

This is the official repository for our paper: HMGAN: A Hierarchical Multi-Modal Generative Adversarial Network Model for Wearable Human Activity Recognition

framework

Dependencies

  • python 3.8
  • torch == 1.10.0 (with suitable CUDA and CuDNN version)
  • numpy, torchmetrics, scipy, pandas, argparse, sklearn

Datasets

Dataset Download Link
UTD-MHAD https://personal.utdallas.edu/~kehtar/UTD-MHAD.html
UCI-HAR https://archive.ics.uci.edu/ml/datasets/human+activity+recognition+using+smartphones
OPPORTUNITY https://archive.ics.uci.edu/ml/datasets/opportunity+activity+recognition

Quick Start

Data preprocessing is included in main.py. Download the datasets and run HMGAN as follows. This gives the performance of each split in 5-fold cross-validation, and their average.

python main.py --data_path [/path/to/dataset] --dataset [UTD_MHAD_arm, UCI_HAR, or OPPORTUNITY]