Xiang-Xiang Su — accepted AI-conference papers

2026

BiEvLight: Bi-level Learning of Task-Aware Event Refinement for Low-Light Image Enhancement

Zishu Yao, Xiang-Xiang Su, Shengning Zhou, Guang-Yong Chen, Guodong Fan, Xing Chen

CVPR 2026

Event cameras, with their high dynamic range, show great promise for Low-light Image Enhancement (LLIE). Existing works primarily focus on designing effective modal fusion strategies. However, a key challenge is the dual degradation from intrinsic background activity (BA) noise in events and low sig

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2026

Bridging Optimization and Neural Networks for Efficient Multi-view Clustering

Huilang Xu, Xiang-Xiang Su, Simin Chen, Guang-Yong Chen, Xing Chen

AAAI 2026technical

Multi-view clustering (MVC) seeks to uncover the intrinsic group structures embedded in multi-view data, which has attracted considerable attention in recent years. Existing approaches predominantly concentrate on incorporating suitable model priors to capture consistency across views. However, thes

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