Congchao Zhu — accepted AI-conference papers

2026

Bi-Bridge: Bidirectional Diffusion Bridges for Low-Light Image Enhancement

Zeyu Hua, Hui Li, Yu Wang, Song Wang, Congchao Zhu, Caixia Zheng

CVPR 2026

Low-Light Image Enhancement (LLIE) is a challenging task, as severe information loss means a single input can correspond to multiple plausible restorations. This inherent ambiguity causes conventional regression-based models to produce overly-smooth results that lack detail. While recent generative

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2025

Acquire and then Adapt: Squeezing out Text-to-Image Model for Image Restoration

Junyuan Deng, Xinyi Wu, Yongxing Yang, Congchao Zhu, Song Wang, Zhenyao Wu

CVPR 2025poster

Recently, pre-trained text-to-image (T2I) models have been extensively adopted for real-world image restoration because of their powerful generative prior. However, controlling these large models for image restoration usually requires a large number of high-quality images and immense computational r…

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