OpenGait: Revisiting Gait Recognition Toward Better Practicality

Chao Fan1; Junhao Liang1; Chuanfu Shen2; Saihui Hou3; Yongzhen Huang3; Shiqi Yu1

10.1109/CVPR52729.2023.00936

2023

1063-6919

979-8-3503-0130-4

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

2023-June

9707-9716

17-24 June 2023

Vancouver, BC, Canada

Gait recognition is one of the most critical long-distance identification technologies and increasingly gains popularity in both research and industry communities. Despite the significant progress made in indoor datasets, much evidence shows that gait recognition techniques perform poorly in the wild. More importantly, we also find that some conclusions drawn from indoor datasets cannot be generalized to real applications. Therefore, the primary goal of this paper is to present a comprehensive benchmark study for better practicality rather than only a particular model for better performance. To this end, we first develop a flexible and efficient gait recognition codebase named OpenGait. Based on OpenGait, we deeply revisit the recent development of gait recognition by re-conducting the ablative experiments. Encouragingly, we detect some unperfect parts of certain prior woks, as well as new insights. Inspired by these discoveries, we develop a structurally simple, empirically powerful, and practically robust baseline model, Gait-Base. Experimentally, we comprehensively compare Gait-Base with many current gait recognition methods on multiple public datasets, and the results reflect that GaitBase achieves significantly strong performance in most cases regardless of indoor or outdoor situations. Code is available at https://github.com/ShiqiYu/OpenGait.

Biometrics

第一

CPCI-S ; EI

WOS:001062522102002

20234114867000

IEEE

1.Department of Computer Science and Engineering, Southern University of Science and Technology
2.Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong
3.School of Artificial Intelligence, Beijing Normal University

Chao Fan,Junhao Liang,Chuanfu Shen,et al. OpenGait: Revisiting Gait Recognition Toward Better Practicality[C],2023:9707-9716.