36 citations · 106 across the 8 of their papers we have counts for
8 papers
Reinforced Diffusion: Learning to Push the Limits of Anisotropic Diffusion for Image Denoising
Xinran Qin, Yuhui Quan, Ruotao Xu +1
Image denoising is an important problem in low-level vision and serves as a critical module for many image recovery tasks. Anisotropic diffusion is a wide family of image denoising…
Astronomical image denoising by self-supervised deep learning and restoration processes
Tie Liu, Yuhui Quan, Yingna Su +9
Image denoising based on deep learning has witnessed significant advancements in recent years. However, existing deep learning methods lack quantitative control of the deviation or…
A Dataset-free Deep learning Method for Low-Dose CT Image Reconstruction
Qiaoqiao Ding, Hui Ji, Yuhui Quan +1
Low-dose CT (LDCT) imaging attracted a considerable interest for the reduction of the object's exposure to X-ray radiation. In recent years, supervised deep learning (DL) has been…
Gaussian Kernel Mixture Network for Single Image Defocus Deblurring
Yuhui Quan, Zicong Wu, Hui Ji
Defocus blur is one kind of blur effects often seen in images, which is challenging to remove due to its spatially variant amount. This paper presents an end-to-end deep learning a…
Recurrent Exposure Generation for Low-Light Face Detection
Jinxiu Liang, Jingwen Wang, Yuhui Quan +4
Face detection from low-light images is challenging due to limited photos and inevitable noise, which, to make the task even harder, are often spatially unevenly distributed. A nat…
Deep Bilateral Retinex for Low-Light Image Enhancement
Jinxiu Liang, Yong Xu, Yuhui Quan +3
Low-light images, i.e. the images captured in low-light conditions, suffer from very poor visibility caused by low contrast, color distortion and significant measurement noise. Low…
UG Track 2: A Collective Benchmark Effort for Evaluating and Advancing Image Understanding in Poor Visibility Environments
Ye Yuan, Wenhan Yang, Wenqi Ren +3
The UG challenge in IEEE CVPR 2019 aims to evoke a comprehensive discussion and exploration about how low-level vision techniques can benefit the high-level automatic visual…
Image Cartoon-Texture Decomposition Using Isotropic Patch Recurrence
Ruotao Xu, Yuhui Quan, Yong Xu
Aiming at separating the cartoon and texture layers from an image, cartoon-texture decomposition approaches resort to image priors to model cartoon and texture respectively. In rec…