Liangtai Zhou — accepted AI-conference papers

2026

Diffusion Once and Done: Degradation-Aware LoRA for All-in-One Image Restoration

Ni Tang, Xiaotong Luo, Zihan Cheng, Liangtai Zhou, Dongxiao Zhang, Yanyun Qu

AAAI 2026technical

Diffusion models have revealed powerful potential in all-in-one image restoration (AiOIR), which is talented in generating abundant texture details. The existing AiOIR methods either retrain a diffusion model or fine-tune the pretrained diffusion model with extra conditional guidance. However, they

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2026

UniLDiff: Unlocking the Power of Diffusion Priors for All-in-One Image Restoration

Zihan Cheng, Liangtai Zhou, Dian Chen, Ni Tang, Xiaotong Luo, Yuan Xie +1

CVPR 2026

All-in-One Image Restoration (AiOIR) has emerged as a promising yet challenging research direction. To address the core challenges of diverse degradation modeling and detail preservation, we propose UniLDiff, a unified framework enhanced with degradation- and detail-aware mechanisms, unlocking the p

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