Learning A Unified Template for Gait Recognition
"What I cannot create, I do not understand."Human wisdom reveals that creation is one of the highest forms of learning. For example, Diffusion Models have demonstrated remarkable semantic structure and memory in image generation, understanding, and restoration, which intuitively benefits representation learning. However, current gait networks rarely embrace this perspective, relying primarily on learning by contrasting gait samples under varying complex conditions, leading to semantic inconsistency and uniformity issues. To address these issues, we propose Origins with generative capabilities whose underlying philosophy is that different entities are generated from a unified template, inh...
| Authors | Panjian Huang, Saihui Hou, Junzhou Huang et al. |
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| Primary category | cs.CV |
| Published | 16 September 2026 |
| Last updated at source | 16 September 2026 |
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