GGCN: Gait Recognition with Generate Network and Convolutional Neural Network

Jan 1, 2026·
秦皓
秦皓
Equal contribution
,
Zhenxue Chen
Equal contribution
,
Qingqiang Guo
,
Q. M. Jonathan Wu
,
Mengxu Lu
· 1 min read
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
publications

GGCN targets robust gait recognition under multiple covariates by separating low-level feature extraction, encoding, and feature mapping.

Gait Recognition Computer Vision Deep Learning
秦皓
Authors
秦皓
Ph.D. Student at Zhejiang University

I am a Ph.D. student in the College of Computer Science and Technology at Zhejiang University. My research focuses on spatial intelligence, 3D-AIGC, multi-agent systems, latent reasoning for VLMs, and contrastive learning, with a broader interest in building intelligent systems that connect perception, reasoning, and controllable creation in the world.

Email: haoqin@zju.edu.cn