BigGait: Learning Gait Representation You Want by Large Vision Models

Dingqiang Ye1,2; Chao Fan1,2; Jingzhe Ma1,2; Xiaoming Liu3; Shiqi Yu1,2

10.1109/CVPR52733.2024.00027

2024-06-22

1063-6919

979-8-3503-5301-3

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

16-22 June 2024

Seattle, WA, USA

Gait recognition stands as one of the most pivotal remote identification technologies and progressively expands across research and industry communities. However, existing gait recognition methods heavily rely on task-specific upstream driven by supervised learning to provide explicit gait representations like silhouette sequences, which in-evitably introduce expensive annotation costs and poten-tial error accumulation. Escaping from this trend, this work explores effective gait representations based on the all-purpose knowledge produced by task-agnostic Large Vision Models (LVMs) and proposes a simple yet efficient gait framework, termed B igGait. Specifically, the Gait Repre-sentation Extractor (GRE) within BigGait draws upon design principles from established gait representations, effectively transforming all-purpose knowledge into implicit gait representations without requiring third-party supervision signals. Experiments on CCPG, CAISA-B* and SUSTechlK indicate that BigGait significantly outperforms the previous methods in both within-domain and cross-domain tasks in most cases, and provides a more practical paradigm for learning the next-generation gait representation. Fi-nally, we delve into prospective challenges and promising directions in LVMs-based gait recognition, aiming to in-spire future work in this emerging topic. The source code is available at https://github.com/ShiqiYu/OpenGait.

第一

1.Research Institute of Trustworthy Autonomous System, Southern University of Science and Technology, Shenzhen, China
2.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
3.Michigan State University, Michigan, United States

Dingqiang Ye,Chao Fan,Jingzhe Ma,et al. BigGait: Learning Gait Representation You Want by Large Vision Models[C],2024.