7 citations · 7 across the 2 of their papers we have counts for
4 papers
DeblurDiff: Real-World Image Deblurring with Generative Diffusion Models
Lingshun Kong, Jiawei Zhang, Dongqing Zou +4
Diffusion models have achieved significant progress in image generation. The pre-trained Stable Diffusion (SD) models are helpful for image deblurring by providing clear image prio…
Efficient Frequency Domain-based Transformers for High-Quality Image Deblurring
Lingshun Kong, Jiangxin Dong, Mingqiang Li +2
We present an effective and efficient method that explores the properties of Transformers in the frequency domain for high-quality image deblurring. Our method is motivated by the…
Deep Blind Video Super-resolution
Jinshan Pan, Songsheng Cheng, Jiawei Zhang +1
Existing video super-resolution (SR) algorithms usually assume that the blur kernels in the degradation process are known and do not model the blur kernels in the restoration. Howe…
Physics-Based Generative Adversarial Models for Image Restoration and Beyond
Jinshan Pan, Jiangxin Dong, Yang Liu +5
We present an algorithm to directly solve numerous image restoration problems (e.g., image deblurring, image dehazing, image deraining, etc.). These problems are highly ill-posed,…