Description

Our code is built on an open source repositoryOpenGait. This is the code for the paper GaitMM: Multi-Granularity Motion Sequence Learning for Gait Recognition.

Operating Environments

Hardware Environment

Our code is running on a server with 2 GeForce RTX 3090 GPUs and a CPU model Intel(R) Core(TM) i7-9800X @ 3.80GHz.

Software Environment

• pytorch = 1.10
• torchvision
• pyyaml
• tensorboard
• opencv-python
• tqdm

Code with Comments

To make the code easier to read, we have collated the model code and added comments. The model code is lib/modeling/models/GaitFM.py. We also give the configuration file code for the training model.

For the CASIA-B dataset

The configuration file is config/gaitfm.yaml.

For the OUMVLP dataset

The configuration file is config/gaitfm_OUMVLP.yaml.

Citation

@inproceedings{wang2023gaitmm,
  title={GAITMM: Multi-Granularity Motion Sequence Learning for Gait Recognition},
  author={Wang, Lei and Liu, Bo and Wang, Bincheng and Yu, Fuqiang},
  booktitle={2023 IEEE International Conference on Image Processing (ICIP)},
  pages={845--849},
  year={2023},
  organization={IEEE}
}