Zzier
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* Update ParsingGait * Clear up the confusion Clear up the confusion about gait3d and gait3d-parsing. * Update 0.get_started.md * Add BaseParsingCuttingTransform * Update gcn.py * Create gaitbase_gait3d_parsing_btz32x2_fixed.yaml * Add gait3d_parsing config file * Update 1.model_zoo.md Update Gait3D-Parsing checkpoints * Update 1.model_zoo.md add configuration * Update 1.model_zoo.md center text --------- Co-authored-by: Junhao Liang <43094337+darkliang@users.noreply.github.com>
📣📣📣 SUSTech1K relseased, pls checking the tutorial. 📣📣📣
🎉🎉🎉 OpenGait has been accpected by CVPR2023 as a highlight paper！ 🎉🎉🎉
OpenGait is a flexible and extensible gait recognition project provided by the Shiqi Yu Group and supported in part by WATRIX.AI.
What's New
- [Oct 2023] Several representative pose-based methods are supported in opengait/modeling/models. This feature is mainly inherited from FastPoseGait. Many thanks to the contributors😊.
- [July 2023] CCPG is supported in datasets/CCPG.
- [July 2023] SUSTech1K is released and supported in datasets/SUSTech1K.
- [May 2023] A real gait recognition system All-in-One-Gait provided by Dongyang Jin is available.
- [Apr 2023] CASIA-E is supported by OpenGait.
- [Feb 2023] HID 2023 competition is open, welcome to participate. Additionally, the tutorial for the competition has been updated in datasets/HID/.
- [Dec 2022] Dataset Gait3D is supported in datasets/Gait3D.
- [Mar 2022] Dataset GREW is supported in datasets/GREW.
Our Publications
- [TPAMI 2023] Learning Gait Representation from Massive Unlabelled Walking Videos: A Benchmark, Paper, Dataset and Code(Coming soon).
- [CVPR 2023] LidarGait: Benchmarking 3D Gait Recognition with Point Clouds, Paper, Dataset and Code.
- [CVPR 2023 Highlight] OpenGait: Revisiting Gait Recognition Toward Better Practicality, Paper, Code.
- [ECCV 2022] GaitEdge: Beyond Plain End-to-end Gait Recognition for Better Practicality, Paper, Code.
A Real Gait Recognition System: All-in-One-Gait
The workflow of All-in-One-Gait involves the processes of pedestrian tracking, segmentation and recognition. See here for details.
Highlighted features
- Mutiple Dataset supported: CASIA-B, OUMVLP, SUSTech1K, HID, GREW, Gait3D, CCPG, and CASIA-E.
- Multiple Models Support: We reproduced several SOTA methods and reached the same or even better performance.
- DDP Support: The officially recommended
Distributed Data Parallel (DDP)mode is used during both the training and testing phases. - AMP Support: The
Auto Mixed Precision (AMP)option is available. - Nice log: We use
tensorboardandloggingto log everything, which looks pretty.
Getting Started
Please see 0.get_started.md. We also provide the following tutorials for your reference:
Model Zoo
Results of appearance-based gait recognition are available here.
Results of pose-based gait recognition are available here.
Authors:
Open Gait Team (OGT)
- Chao Fan (樊超), 12131100@mail.sustech.edu.cn
- Chuanfu Shen (沈川福), 11950016@mail.sustech.edu.cn
- Junhao Liang (梁峻豪), 12132342@mail.sustech.edu.cn
Acknowledgement
-
GLN: Saihui Hou (侯赛辉)
-
GaitGL: Beibei Lin (林贝贝)
-
GREW: GREW TEAM
-
FastPoseGait Team: FastPoseGait Team
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.