GGCN: Gait Recognition with Generate Network and Convolutional Neural Network
Jan 1, 2026·
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1 min read
Hao Qin
Zhenxue Chen
Qingqiang Guo
Q. M. Jonathan Wu
Mengxu Lu
Abstract
GGCN is a robust gait recognition model that uses a generate network, encoder network, and feature mapping network to reduce covariate interference and learn more discriminative gait representations.
Type
Publication
Journal of Visual Communication and Image Representation
GGCN targets robust gait recognition under multiple covariates by separating low-level feature extraction, encoding, and feature mapping.
Authors
Ph.D. Student in Artificial Intelligence
I am a Ph.D. student in the College of Computer Science and Technology at
Zhejiang University. My research focuses on 3D vision, 3D Gaussian Splatting,
3D-AIGC, and multi-agent systems, with broader interests in self-supervised
representation learning and embodied visual content creation.