Author

Xiaoming Liu

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Preprint Sep 2026

Restore What Matters: Lessons from Joint Restoration and Recognition

Recognition pipelines typically adopt a restore-then-recognize workflow, yet decades of experience show that generating visually pleasing images seldom translates to improved recognition. We propose a Joint Restoration-for-Recognition (JR$^2$) paradigm: restore only what downstream tasks truly require, with task signal...

Lan-Qing Guo, Xi-Jun Wang, Minchul Kim et al. · 0 citations

Preprint Aug 2026

SapiensID 2.0: Aligning Human Recognition Foundation Models with Human Perception

This work proposes SapiensID 2.0, a human recognition framework enriched with both semantic and temporal awareness that achieves state-of-the-art performance across image- and video-based person re-identification and gait recognition, while maintaining robust face recognition capabilities.

Yi-Yang Su, Jie Zhu, Feng Liu et al. · 1 citation