3 citations · 4 across the 5 of their papers we have counts for
5 papers · 1 filter
Diffusion Once and Done: Degradation-Aware LoRA for Efficient All-in-One Image Restoration
Ni Tang, Xiaotong Luo, Zihan Cheng +3
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 eith…
UniLDiff: Unlocking the Power of Diffusion Priors for All-in-One Image Restoration
Zihan Cheng, Liangtai Zhou, Dian Chen +3
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 preser…
Data-free Distillation with Degradation-prompt Diffusion for Multi-weather Image Restoration
Pei Wang, Xiaotong Luo, Yuan Xie +1
Multi-weather image restoration has witnessed incredible progress, while the increasing model capacity and expensive data acquisition impair its applications in memory-limited devi…
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
Shanxin Yuan, Radu Timofte, Ales Leonardis +43
This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. Demo…
Bi-GANs-ST for Perceptual Image Super-resolution
Xiaotong Luo, Rong Chen, Yuan Xie +2
Image quality measurement is a critical problem for image super-resolution (SR) algorithms. Usually, they are evaluated by some well-known objective metrics, e.g., PSNR and SSIM, b…