most citedExploring Deep Models for Practical Gait Recognition

17 citations · 27 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023★ 1 cited

Pedestrian Attribute Editing for Gait Recognition and Anonymization

Jingzhe Ma, Dingqiang Ye, Chao Fan +1

As a kind of biometrics, the gait information of pedestrians has attracted widespread attention from both industry and academia since it can be acquired from long distances without…

cs.CV2023★ 17 cited

Exploring Deep Models for Practical Gait Recognition

Chao Fan, Saihui Hou, Yongzhen Huang +1

Gait recognition is a rapidly advancing vision technique for person identification from a distance. Prior studies predominantly employed relatively shallow networks to extract subt…

cs.CV2022★ 5 cited

OpenGait: Revisiting Gait Recognition Toward Better Practicality

Chao Fan, Junhao Liang, Chuanfu Shen +3

Gait recognition is one of the most critical long-distance identification technologies and increasingly gains popularity in both research and industry communities. Despite the sign…

cs.CV2022★ 1 cited

Learning Gait Representation from Massive Unlabelled Walking Videos: A Benchmark

Chao Fan, Saihui Hou, Jilong Wang +2

Gait depicts individuals' unique and distinguishing walking patterns and has become one of the most promising biometric features for human identification. As a fine-grained recogni…

cs.CV2022★ 3 cited

GaitEdge: Beyond Plain End-to-end Gait Recognition for Better Practicality

Junhao Liang, Chao Fan, Saihui Hou +3

Gait is one of the most promising biometrics to identify individuals at a long distance. Although most previous methods have focused on recognizing the silhouettes, several end-to-…