13 citations · 14 across the 8 of their papers we have counts for
8 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…
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution
Xinyi Liu, Feiyu Tan, Qi Xie +2
Burst image processing (BIP), which captures and integrates multiple frames into a single high-quality image, is widely used in consumer cameras. As a typical BIP task, Burst Image…
Enhancing Underwater Imaging with 4-D Light Fields: Dataset and Method
Yuji Lin, Junhui Hou, Xianqiang Lyu +2
In this paper, we delve into the realm of 4-D light fields (LFs) to enhance underwater imaging plagued by light absorption, scattering, and other challenges. Contrasting with conve…
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…
Guided Image Restoration via Simultaneous Feature and Image Guided Fusion
Xinyi Liu, Qian Zhao, Jie Liang +3
Guided image restoration (GIR), such as guided depth map super-resolution and pan-sharpening, aims to enhance a target image using guidance information from another image of the sa…
Nonparametric Prior Learning in Differential Equation Modeling
Junxiong Jia, Deyu Meng, Zongben Xu +1
This paper addresses Bayesian inference related to partial differential equations (PDEs), particularly nonparametric regression constrained by PDEs. To effectively encode prior inf…
Variational Bayes' method for functions with applications to some inverse problems
Junxiong Jia, Qian Zhao, Zongben Xu +2
Bayesian approach, as a useful tool for quantifying uncertainties, has been widely used for solving inverse problems of partial differential equations (PDEs). One of the key diffic…