Home

Awesome

<img src="./assets/logo2.png" width = "320" height = "110" alt="logo" /> <div align="center"><img src="./assets/nm.gif" width = "100" height = "100" alt="nm" /><img src="./assets/bg.gif" width = "100" height = "100" alt="bg" /><img src="./assets/cl.gif" width = "100" height = "100" alt="cl" /></div>
<!-- 📣📣📣 **[*GaitLU-1M*](https://ieeexplore.ieee.org/document/10242019) relseased, pls checking the [tutorial](datasets/GaitLU-1M/README.md).** 📣📣📣 📣📣📣 **[*SUSTech1K*](https://lidargait.github.io) relseased, pls checking the [tutorial](datasets/SUSTech1K/README.md).** 📣📣📣 🎉🎉🎉 **[*OpenGait*](https://openaccess.thecvf.com/content/CVPR2023/papers/Fan_OpenGait_Revisiting_Gait_Recognition_Towards_Better_Practicality_CVPR_2023_paper.pdf) has been accpected by CVPR2023 as a highlight paper！** 🎉🎉🎉 -->

OpenGait is a flexible and extensible gait analysis project provided by the Shiqi Yu Group and supported in part by WATRIX.AI. The corresponding paper has been accepted by CVPR2023 as a highlight paper.

What's New

<!--- [Dec 2023] A new state-of-the-art baseline, i.e., [DeepGaitV2](https://arxiv.org/pdf/2303.03301.pdf), is available at [here](opengait/modeling/models/deepgaitv2.py)! --> <!-- - [Nov 2023] The first million-level unlabeled gait dataset, i.e., [GaitLU-1M](https://ieeexplore.ieee.org/document/10242019), is released and supported in [datasets/GaitLU-1M](datasets/GaitLU-1M/README.md). - [Oct 2023] Several representative pose-based methods are supported in [opengait/modeling/models](./opengait/modeling/models). This feature is mainly inherited from [FastPoseGait](https://github.com/BNU-IVC/FastPoseGait). Many thanks to the contributors😊. - [July 2023] [CCPG](https://github.com/BNU-IVC/CCPG) is supported in [datasets/CCPG](./datasets/CCPG). --> <!-- - - - [July 2023] [SUSTech1K](https://lidargait.github.io) is released and supported in [datasets/SUSTech1K](./datasets/SUSTech1K). [May 2023] A real gait recognition system [All-in-One-Gait](https://github.com/jdyjjj/All-in-One-Gait) provided by [Dongyang Jin](https://github.com/jdyjjj) is available. [Apr 2023] [CASIA-E](datasets/CASIA-E/README.md) is supported by OpenGait. - [Feb 2023] [HID 2023 competition](https://hid2023.iapr-tc4.org/) is open, welcome to participate. Additionally, the tutorial for the competition has been updated in [datasets/HID/](./datasets/HID). - [Dec 2022] Dataset [Gait3D](https://github.com/Gait3D/Gait3D-Benchmark) is supported in [datasets/Gait3D](./datasets/Gait3D). - [Mar 2022] Dataset [GREW](https://www.grew-benchmark.org) is supported in [datasets/GREW](./datasets/GREW). -->

Our Publications

A Real Gait Recognition System: All-in-One-Gait

<div align="center"> <img src="./assets/probe1-After.gif" width = "455" height = "256" alt="probe1-After" /> </div>

The workflow of All-in-One-Gait involves the processes of pedestrian tracking, segmentation and recognition. See here for details.

Highlighted features

Getting Started

Please see 0.get_started.md. We also provide the following tutorials for your reference:

Model Zoo

✨✨✨You can find all the checkpoint files at Hugging Face Models✨✨✨!

The result list of appearance-based gait recognition is available here.

The result list of pose-based gait recognition is available here.

Authors:

Now OpenGait is mainly maintained by Dongyang Jin (金冬阳), 11911221@mail.sustech.edu.cn

Acknowledgement

Citation

@InProceedings{Fan_2023_CVPR,
    author    = {Fan, Chao and Liang, Junhao and Shen, Chuanfu and Hou, Saihui and Huang, Yongzhen and Yu, Shiqi},
    title     = {OpenGait: Revisiting Gait Recognition Towards Better Practicality},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2023},
    pages     = {9707-9716}
}

Note: This code is only used for academic purposes, people cannot use this code for anything that might be considered commercial use.