62 citations · 284 across the 21 of their papers we have counts for
21 papers
Synthesizing Realistic Image Restoration Training Pairs: A Diffusion Approach
Tao Yang, Peiran Ren, Xuansong xie +1
In supervised image restoration tasks, one key issue is how to obtain the aligned high-quality (HQ) and low-quality (LQ) training image pairs. Unfortunately, such HQ-LQ training pa…
Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer
Yuang Ai, Xiaoqiang Zhou, Huaibo Huang +2
Unsupervised Domain Adaptation (UDA) can effectively address domain gap issues in real-world image Super-Resolution (SR) by accessing both the source and target data. Considering p…
Spatial-Frequency Attention for Image Denoising
Shi Guo, Hongwei Yong, Xindong Zhang +2
The recently developed transformer networks have achieved impressive performance in image denoising by exploiting the self-attention (SA) in images. However, the existing methods m…
Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-Resolution
Ruohao Wang, Xiaohui Liu, Zhilu Zhang +4
Video super-resolution (VSR) aiming to reconstruct a high-resolution (HR) video from its low-resolution (LR) counterpart has made tremendous progress in recent years. However, it r…
From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution
Xiaoming Li, Chaofeng Chen, Xianhui Lin +2
How to design proper training pairs is critical for super-resolving real-world low-quality (LQ) images, which suffers from the difficulties in either acquiring paired ground-truth…
A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution
Jianqi Ma, Zhetong Liang, Lei Zhang
Scene text image super-resolution aims to increase the resolution and readability of the text in low-resolution images. Though significant improvement has been achieved by deep con…
A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift
Shi Guo, Xi Yang, Jianqi Ma +2
Denoising and demosaicking are two essential steps to reconstruct a clean full-color image from the raw data. Recently, joint denoising and demosaicking (JDD) for burst images, nam…
Efficient Long-Range Attention Network for Image Super-resolution
Xindong Zhang, Hui Zeng, Shi Guo +1
Recently, transformer-based methods have demonstrated impressive results in various vision tasks, including image super-resolution (SR), by exploiting the self-attention (SA) for f…
Unfolded Deep Kernel Estimation for Blind Image Super-resolution
Hongyi Zheng, Hongwei Yong, Lei Zhang
Blind image super-resolution (BISR) aims to reconstruct a high-resolution image from its low-resolution counterpart degraded by unknown blur kernel and noise. Many deep neural netw…
Image-Adaptive YOLO for Object Detection in Adverse Weather Conditions
Wenyu Liu, Gaofeng Ren, Runsheng Yu +3
Though deep learning-based object detection methods have achieved promising results on the conventional datasets, it is still challenging to locate objects from the low-quality ima…
SVBRDF Recovery From a Single Image With Highlights using a Pretrained Generative Adversarial Network
Tao Wen, Beibei Wang, Lei Zhang +2
Spatially-varying bi-directional reflectance distribution functions (SVBRDFs) are crucial for designers to incorporate new materials in virtual scenes, making them look more realis…
Text Prior Guided Scene Text Image Super-resolution
Jianqi Ma, Shi Guo, Lei Zhang
Scene text image super-resolution (STISR) aims to improve the resolution and visual quality of low-resolution (LR) scene text images, and consequently boost the performance of text…
High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network
Jie Liang, Hui Zeng, Lei Zhang
Existing image-to-image translation (I2IT) methods are either constrained to low-resolution images or long inference time due to their heavy computational burden on the convolution…
PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency
Jie Liang, Hui Zeng, Miaomiao Cui +2
Different from general photo retouching tasks, portrait photo retouching (PPR), which aims to enhance the visual quality of a collection of flat-looking portrait photos, has its sp…
GAN Prior Embedded Network for Blind Face Restoration in the Wild
Tao Yang, Peiran Ren, Xuansong Xie +1
Blind face restoration (BFR) from severely degraded face images in the wild is a very challenging problem. Due to the high illness of the problem and the complex unknown degradatio…
HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset
Guanying Chen, Chaofeng Chen, Shi Guo +3
High dynamic range (HDR) video reconstruction from sequences captured with alternating exposures is a very challenging problem. Existing methods often align low dynamic range (LDR)…
Joint Denoising and Demosaicking with Green Channel Prior for Real-world Burst Images
Shi Guo, Zhetong Liang, Lei Zhang
Denoising and demosaicking are essential yet correlated steps to reconstruct a full color image from the raw color filter array (CFA) data. By learning a deep convolutional neural…
Grid Anchor based Image Cropping: A New Benchmark and An Efficient Model
Hui Zeng, Lida Li, Zisheng Cao +1
Image cropping aims to improve the composition as well as aesthetic quality of an image by removing extraneous content from it. Most of the existing image cropping databases provid…
CameraNet: A Two-Stage Framework for Effective Camera ISP Learning
Zhetong Liang, Jianrui Cai, Zisheng Cao +1
Traditional image signal processing (ISP) pipeline consists of a set of individual image processing components onboard a camera to reconstruct a high-quality sRGB image from the se…
Toward Convolutional Blind Denoising of Real Photographs
Shi Guo, Zifei Yan, Kai Zhang +2
While deep convolutional neural networks (CNNs) have achieved impressive success in image denoising with additive white Gaussian noise (AWGN), their performance remains limited on…
A Probabilistic Quality Representation Approach to Deep Blind Image Quality Prediction
Hui Zeng, Lei Zhang, Alan C. Bovik
Blind image quality assessment (BIQA) remains a very challenging problem due to the unavailability of a reference image. Deep learning based BIQA methods have been attracting incre…