This repository contains the source code and additional resources for our paper titled "GAF-Net: Gait-Appearance Fusion Network for Video-Based Person Re-Identification". Our work introduces GAF-Net, a novel approach that integrates appearance with gait features, extracted from skeletal structures, to enhance the performance of person re-identification systems.
src/: Source code of the GAF-Net model.data/: Example datasets and instructions on how to prepare the data.models/: Pre-trained models and configuration files.notebooks/: Jupyter notebooks demonstrating the usage and results of the model.docs/: Additional documentation and resources.
Instructions on setting up the environment and installing dependencies will be provided here.
Detailed instructions on how to use the model, including training and inference processes, will be added.
Guidelines for contributing to this repository will be available here.
If you find our work useful in your research, please consider citing:
[Appropriate license details]
For any queries regarding the code or the paper, feel free to reach out to us.
This README and the associated repository are currently under construction and will be updated with more information soon.