1 code implementation • 18 May 2023 • Xiangyu Rui, Xiangyong Cao, Zeyu Zhu, Zongsheng Yue, Deyu Meng
Specifically, we assume that the HRMS image is decomposed into the product of two low-rank tensors, i. e., the base tensor and the coefficient matrix.
no code implementations • 11 May 2023 • Jianyi Wang, Zongsheng Yue, Shangchen Zhou, Kelvin C. K. Chan, Chen Change Loy
We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution (SR).
1 code implementation • 13 Dec 2022 • Zongsheng Yue, Chen Change Loy
Moreover, the transition distribution can contract the error of the restoration backbone and thus makes our method more robust to unknown degradations.
Ranked #5 on
Blind Face Restoration
on CelebA-Test
1 code implementation • CVPR 2022 • Zongsheng Yue, Qian Zhao, Jianwen Xie, Lei Zhang, Deyu Meng, Kwan-Yee K. Wong
To address the above issues, this paper proposes a model-based blind SISR method under the probabilistic framework, which elaborately models image degradation from the perspectives of noise and blur kernel.
no code implementations • CVPR 2021 • Xiangyu Rui, Xiangyong Cao, Qi Xie, Zongsheng Yue, Qian Zhao, Deyu Meng
A general approach for handling hyperspectral image (HSI) denoising issue is to impose weights on different HSI pixels to suppress negative influence brought by noisy elements.
no code implementations • 5 Jun 2021 • Hui Wang, Zongsheng Yue, Qian Zhao, Deyu Meng
Under this framework, the posterior of the latent clean image and blur kernel can be jointly estimated in an amortized inference fashion with DNNs, and the involved inference DNNs can be trained by fully considering the physical blur model, together with the supervision of data driven priors for the clean image and blur kernel, which is naturally led to by the evidence lower bound objective.
1 code implementation • CVPR 2021 • Zongsheng Yue, Jianwen Xie, Qian Zhao, Deyu Meng
Firstly, most of them do not sufficiently model the characteristics of rain layers of rainy videos.
2 code implementations • 25 Aug 2020 • Zongsheng Yue, Hongwei Yong, Qian Zhao, Lei Zhang, Deyu Meng, Kwan-Yen K. Wong
In this proposed model, a pixel-wise non-i. i. d.
1 code implementation • CVPR 2021 • Hong Wang, Zongsheng Yue, Qi Xie, Qian Zhao, Yefeng Zheng, Deyu Meng
For the single image rain removal (SIRR) task, the performance of deep learning (DL)-based methods is mainly affected by the designed deraining models and training datasets.
2 code implementations • ECCV 2020 • Zongsheng Yue, Qian Zhao, Lei Zhang, Deyu Meng
Specifically, we approximate the joint distribution with two different factorized forms, which can be formulated as a denoiser mapping the noisy image to the clean one and a generator mapping the clean image to the noisy one.
Ranked #8 on
Image Denoising
on DND
(using extra training data)
2 code implementations • NeurIPS 2019 • Zongsheng Yue, Hongwei Yong, Qian Zhao, Lei Zhang, Deyu Meng
On one hand, as other data-driven deep learning methods, our method, namely variational denoising network (VDN), can perform denoising efficiently due to its explicit form of posterior expression.
Ranked #10 on
Image Denoising
on DND