General image fusion aims to integrate complementary information from multiple source images, but existing methods often rely on task-specific models and struggle to maintain robust performance under diverse degradation conditions. In this paper, we propose UniDiffFusion, a unified diffusion framework for multi-task an...
Xing-Xin Xu, Si-Qi Zhao, Xin Li et al.· 0 citations
Supervised infrared-visible image fusion (IVIF) often overfits limited training distributions, creating a critical generalization gap under open-world degradations (rain, haze, low light, noise, blur). To address this issue, we propose AIR-Fusion, a parameter-efficient adaptation of a frozen, restoration-capable latent...
Bing Cao, Qiang Zhang, Xing-Xin Xu et al.· Proceedings of the Thirty-Fi...· 0 citations
Bridging Literature, Agents, and Zero-gap Experimentation (BLAZE), a paradigm of socialized scientific intelligence, makes discovery more traceable, reproducible, and cumulative while preserving human creativity, judgment, and responsibility.
Xinjie Yao, Xing-Xin Xu, Xi-Yuan Gao et al.· 0 citations
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