54 citations · 523 across the 37 of their papers we have counts for
38 papers
Deep Richardson-Lucy Deconvolution for Low-Light Image Deblurring
Liang Chen, Jiawei Zhang, Zhenhua Li +4
Images taken under the low-light condition often contain blur and saturated pixels at the same time. Deblurring images with saturated pixels is quite challenging. Because of the li…
Deep Dynamic Scene Deblurring from Optical Flow
Jiawei Zhang, Jinshan Pan, Daoye Wang +5
Deblurring can not only provide visually more pleasant pictures and make photography more convenient, but also can improve the performance of objection detection as well as trackin…
Self-Supervised Intensity-Event Stereo Matching
Jinjin Gu, Jinan Zhou, Ringo Sai Wo Chu +5
Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption. Despite t…
NTIRE 2022 Challenge on Perceptual Image Quality Assessment
Jinjin Gu, Haoming Cai, Chao Dong +2
This paper reports on the NTIRE 2022 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (…
A New Journey from SDRTV to HDRTV
Xiangyu Chen, Zhengwen Zhang, Jimmy S. Ren +3
Nowadays modern displays are capable to render video content with high dynamic range (HDR) and wide color gamut (WCG). However, most available resources are still in standard dynam…
NTIRE 2021 Challenge on Perceptual Image Quality Assessment
Jinjin Gu, Haoming Cai, Chao Dong +47
This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (…
Low-Dose CT Denoising Using a Structure-Preserving Kernel Prediction Network
Lu Xu, Yuwei Zhang, Ying Liu +5
Low-dose CT has been a key diagnostic imaging modality to reduce the potential risk of radiation overdose to patient health. Despite recent advances, CNN-based approaches typically…
Efficient Deep Image Denoising via Class Specific Convolution
Lu Xu, Jiawei Zhang, Xuanye Cheng +3
Deep neural networks have been widely used in image denoising during the past few years. Even though they achieve great success on this problem, they are computationally inefficien…
Image Quality Assessment for Perceptual Image Restoration: A New Dataset, Benchmark and Metric
Jinjin Gu, Haoming Cai, Haoyu Chen +3
Image quality assessment (IQA) is the key factor for the fast development of image restoration (IR) algorithms. The most recent perceptual IR algorithms based on generative adversa…
EfficientFCN: Holistically-guided Decoding for Semantic Segmentation
Jianbo Liu, Junjun He, Jiawei Zhang +2
Both performance and efficiency are important to semantic segmentation. State-of-the-art semantic segmentation algorithms are mostly based on dilated Fully Convolutional Networks (…
PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration
Jinjin Gu, Haoming Cai, Haoyu Chen +3
Image quality assessment (IQA) is the key factor for the fast development of image restoration (IR) algorithms. The most recent IR methods based on Generative Adversarial Networks…
Learning a Reinforced Agent for Flexible Exposure Bracketing Selection
Zhouxia Wang, Jiawei Zhang, Mude Lin +3
Automatically selecting exposure bracketing (images exposed differently) is important to obtain a high dynamic range image by using multi-exposure fusion. Unlike previous methods t…
Learning Event-Based Motion Deblurring
Zhe Jiang, Yu Zhang, Dongqing Zou +3
Recovering sharp video sequence from a motion-blurred image is highly ill-posed due to the significant loss of motion information in the blurring process. For event-based cameras,…
Learning to Predict Context-adaptive Convolution for Semantic Segmentation
Jianbo Liu, Junjun He, Jimmy S. Ren +2
Long-range contextual information is essential for achieving high-performance semantic segmentation. Previous feature re-weighting methods demonstrate that using global context for…
Dual Student: Breaking the Limits of the Teacher in Semi-supervised Learning
Zhanghan Ke, Daoye Wang, Qiong Yan +2
Recently, consistency-based methods have achieved state-of-the-art results in semi-supervised learning (SSL). These methods always involve two roles, an explicit or implicit teache…
Image Formation Model Guided Deep Image Super-Resolution
Jinshan Pan, Yang Liu, Deqing Sun +4
We present a simple and effective image super-resolution algorithm that imposes an image formation constraint on the deep neural networks via pixel substitution. The proposed algor…
Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline
Guocheng Qian, Yuanhao Wang, Jinjin Gu +4
Imaging is usually a mixture problem of incomplete color sampling, noise degradation, and limited resolution. This mixture problem is typically solved by a sequential solution that…
Generalizing Monocular 3D Human Pose Estimation in the Wild
Luyang Wang, Yan Chen, Zhenhua Guo +4
The availability of the large-scale labeled 3D poses in the Human3.6M dataset plays an important role in advancing the algorithms for 3D human pose estimation from a still image. W…
DAVANet: Stereo Deblurring with View Aggregation
Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo +3
Nowadays stereo cameras are more commonly adopted in emerging devices such as dual-lens smartphones and unmanned aerial vehicles. However, they also suffer from blurry images in dy…
Spatio-Temporal Filter Adaptive Network for Video Deblurring
Shangchen Zhou, Jiawei Zhang, Jinshan Pan +3
Video deblurring is a challenging task due to the spatially variant blur caused by camera shake, object motions, and depth variations, etc. Existing methods usually estimate optica…
Very Power Efficient Neural Time-of-Flight
Yan Chen, Jimmy Ren, Xuanye Cheng +2
Time-of-Flight (ToF) cameras require active illumination to obtain depth information thus the power of illumination directly affects the performance of ToF cameras. Traditional ToF…
DSR: Direct Self-rectification for Uncalibrated Dual-lens Cameras
Ruichao Xiao, Wenxiu Sun, Jiahao Pang +2
With the developments of dual-lens camera modules,depth information representing the third dimension of thecaptured scenes becomes available for smartphones. It isestimated by ster…
Learning Monocular Depth by Distilling Cross-domain Stereo Networks
Xiaoyang Guo, Hongsheng Li, Shuai Yi +2
Monocular depth estimation aims at estimating a pixelwise depth map for a single image, which has wide applications in scene understanding and autonomous driving. Existing supervis…
Physics-Based Generative Adversarial Models for Image Restoration and Beyond
Jinshan Pan, Jiangxin Dong, Yang Liu +5
We present an algorithm to directly solve numerous image restoration problems (e.g., image deblurring, image dehazing, image deraining, etc.). These problems are highly ill-posed,…