212 citations · 319 across the 14 of their papers we have counts for
14 papers
Enhancing Underwater Light Field Images via Global Geometry-aware Diffusion Process
Yuji Lin, Qian Zhao, Zongsheng Yue +2
This work studies the challenging problem of acquiring high-quality underwater images via 4-D light field (LF) imaging. To this end, we propose GeoDiff-LF, a novel diffusion-based…
Generative Latent Kernel Modeling for Blind Motion Deblurring
Chenhao Ding, Jiangtao Zhang, Zongsheng Yue +3
Deep prior-based approaches have demonstrated remarkable success in blind motion deblurring (BMD) recently. These methods, however, are often limited by the high non-convexity of t…
Blind Image Deconvolution by Generative-based Kernel Prior and Initializer via Latent Encoding
Jiangtao Zhang, Zongsheng Yue, Hui Wang +2
Blind image deconvolution (BID) is a classic yet challenging problem in the field of image processing. Recent advances in deep image prior (DIP) have motivated a series of DIP-base…
ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting
Zongsheng Yue, Jianyi Wang, Chen Change Loy
Diffusion-based image super-resolution (SR) methods are mainly limited by the low inference speed due to the requirements of hundreds or even thousands of sampling steps. Existing…
Unsupervised Hyperspectral Pansharpening via Low-rank Diffusion Model
Xiangyu Rui, Xiangyong Cao, Li Pang +3
Hyperspectral pansharpening is a process of merging a high-resolution panchromatic (PAN) image and a low-resolution hyperspectral (LRHS) image to create a single high-resolution hy…
Exploiting Diffusion Prior for Real-World Image Super-Resolution
Jianyi Wang, Zongsheng Yue, Shangchen Zhou +2
We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution (SR). Specifically, by employing our t…
DifFace: Blind Face Restoration with Diffused Error Contraction
Zongsheng Yue, Chen Change Loy
While deep learning-based methods for blind face restoration have achieved unprecedented success, they still suffer from two major limitations. First, most of them deteriorate when…
Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel
Zongsheng Yue, Qian Zhao, Jianwen Xie +3
While researches on model-based blind single image super-resolution (SISR) have achieved tremendous successes recently, most of them do not consider the image degradation sufficien…
A Deep Variational Bayesian Framework for Blind Image Deblurring
Hui Wang, Zongsheng Yue, Qian Zhao +1
Blind image deblurring is an important yet very challenging problem in low-level vision. Traditional optimization based methods generally formulate this task as a maximum-a-posteri…
Semi-Supervised Video Deraining with Dynamical Rain Generator
Zongsheng Yue, Jianwen Xie, Qian Zhao +1
While deep learning (DL)-based video deraining methods have achieved significant success recently, they still exist two major drawbacks. Firstly, most of them do not sufficiently m…
Deep Variational Network Toward Blind Image Restoration
Zongsheng Yue, Hongwei Yong, Qian Zhao +3
Blind image restoration (IR) is a common yet challenging problem in computer vision. Classical model-based methods and recent deep learning (DL)-based methods represent two differe…
From Rain Generation to Rain Removal
Hong Wang, Zongsheng Yue, Qi Xie +3
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. Most o…
Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation
Zongsheng Yue, Qian Zhao, Lei Zhang +1
Real-world image noise removal is a long-standing yet very challenging task in computer vision. The success of deep neural network in denoising stimulates the research of noise gen…
Variational Denoising Network: Toward Blind Noise Modeling and Removal
Zongsheng Yue, Hongwei Yong, Qian Zhao +2
Blind image denoising is an important yet very challenging problem in computer vision due to the complicated acquisition process of real images. In this work we propose a new varia…