A flexible and extensible framework for gait recognition. You can focus on designing your own models and comparing with state-of-the-arts easily with the help of OpenGait.
Python
1,171
304 commits
updated Oct 14, 2026



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. The extension paper has been accepted to TPAMI2025.
The workflow of All-in-One-Gait involves the processes of pedestrian tracking, segmentation and recognition. See here for details.
Distributed Data Parallel (DDP) mode is used during both the training and testing phases.Auto Mixed Precision (AMP) option is available.tensorboard and logging to log everything, which looks pretty.Please see 0.get_started.md. We also provide the following tutorials for your reference:
✨✨✨You can find all the checkpoint files at ✨✨✨!
The result list of appearance-based gait recognition is available here.
The result list of pose-based gait recognition is available here.
Now OpenGait is mainly maintained by Dongyang Jin (金冬阳), [email protected]
GLN: Saihui Hou (侯赛辉)
GaitGL: Beibei Lin (林贝贝)
GREW: GREW TEAM
FastPoseGait Team: FastPoseGait Team
Gait3D Team: Gait3D Team
@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}
}
@ARTICLE{fan2025opengait,
author={Fan, Chao and Hou, Saihui and Liang, Junhao and Shen, Chuanfu and Ma, Jingzhe and Jin, Dongyang and Huang, Yongzhen and Yu, Shiqi},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={OpenGait: A Comprehensive Benchmark Study for Gait Recognition Towards Better Practicality},
year={2025},
volume={},
number={},
pages={1-18},
doi={10.1109/TPAMI.2025.3576283}
}
Note: This code is only used for academic purposes, people cannot use this code for anything that might be considered commercial use.
7,291 followers · starred Sep 2026
641 followers · starred Jan 2022
131 followers · starred Dec 2025
250 followers · starred May 2026
A flexible and extensible framework for gait recognition. You can focus on designing your own models and comparing with state-of-the-arts easily with the help of OpenGait.
Python
1,171
304 commits
updated Oct 14, 2026



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. The extension paper has been accepted to TPAMI2025.
The workflow of All-in-One-Gait involves the processes of pedestrian tracking, segmentation and recognition. See here for details.
Distributed Data Parallel (DDP) mode is used during both the training and testing phases.Auto Mixed Precision (AMP) option is available.tensorboard and logging to log everything, which looks pretty.Please see 0.get_started.md. We also provide the following tutorials for your reference:
✨✨✨You can find all the checkpoint files at ✨✨✨!
The result list of appearance-based gait recognition is available here.
The result list of pose-based gait recognition is available here.
Now OpenGait is mainly maintained by Dongyang Jin (金冬阳), [email protected]
GLN: Saihui Hou (侯赛辉)
GaitGL: Beibei Lin (林贝贝)
GREW: GREW TEAM
FastPoseGait Team: FastPoseGait Team
Gait3D Team: Gait3D Team
@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}
}
@ARTICLE{fan2025opengait,
author={Fan, Chao and Hou, Saihui and Liang, Junhao and Shen, Chuanfu and Ma, Jingzhe and Jin, Dongyang and Huang, Yongzhen and Yu, Shiqi},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={OpenGait: A Comprehensive Benchmark Study for Gait Recognition Towards Better Practicality},
year={2025},
volume={},
number={},
pages={1-18},
doi={10.1109/TPAMI.2025.3576283}
}
Note: This code is only used for academic purposes, people cannot use this code for anything that might be considered commercial use.
7,291 followers · starred Sep 2026
641 followers · starred Jan 2022
131 followers · starred Dec 2025
250 followers · starred May 2026