9.2k citations · 16.2k across the 175 of their papers we have counts for
21 papers · 1 filter
Two-Stage Single Image Reflection Removal with Reflection-Aware Guidance
Yu Li, Ming Liu, Yaling Yi +3
Removing undesired reflection from an image captured through a glass surface is a very challenging problem with many practical application scenarios. For improving reflection remov…
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov, Radu Timofte, Zhilu Zhang +36
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…
Progressive Training of Multi-level Wavelet Residual Networks for Image Denoising
Yali Peng, Yue Cao, Shigang Liu +2
Recent years have witnessed the great success of deep convolutional neural networks (CNNs) in image denoising. Albeit deeper network and larger model capacity generally benefit per…
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei, Hannan Lu, Radu Timofte +68
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…
Learning Flow-based Feature Warping for Face Frontalization with Illumination Inconsistent Supervision
Yuxiang Wei, Ming Liu, Haolin Wang +3
Despite recent advances in deep learning-based face frontalization methods, photo-realistic and illumination preserving frontal face synthesis is still challenging due to large pos…
Learning Spatio-Appearance Memory Network for High-Performance Visual Tracking
Fei Xie, Wankou Yang, Bo Liu +3
Existing visual object tracking usually learns a bounding-box based template to match the targets across frames, which cannot accurately learn a pixel-wise representation, thereby…
Unpaired Learning of Deep Image Denoising
Xiaohe Wu, Ming Liu, Yue Cao +2
We investigate the task of learning blind image denoising networks from an unpaired set of clean and noisy images. Such problem setting generally is practical and valuable consider…
Component Divide-and-Conquer for Real-World Image Super-Resolution
Pengxu Wei, Ziwei Xie, Hannan Lu +4
In this paper, we present a large-scale Diverse Real-world image Super-Resolution dataset, i.e., DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring t…
Blind Face Restoration via Deep Multi-scale Component Dictionaries
Xiaoming Li, Chaofeng Chen, Shangchen Zhou +3
Recent reference-based face restoration methods have received considerable attention due to their great capability in recovering high-frequency details on real low-quality images.…
Plug-and-Play Image Restoration with Deep Denoiser Prior
Kai Zhang, Yawei Li, Wangmeng Zuo +3
Recent works on plug-and-play image restoration have shown that a denoiser can implicitly serve as the image prior for model-based methods to solve many inverse problems. Such a pr…
Lightweight image super-resolution with enhanced CNN
Chunwei Tian, Ruibin Zhuge, Zhihao Wu +4
Deep convolutional neural networks (CNNs) with strong expressive ability have achieved impressive performances on single image super-resolution (SISR). However, their excessive amo…
Designing and Training of A Dual CNN for Image Denoising
Chunwei Tian, Yong Xu, Wangmeng Zuo +3
Deep convolutional neural networks (CNNs) for image denoising have recently attracted increasing research interest. However, plain networks cannot recover fine details for a comple…
Aligning Partially Overlapping Point Sets: an Inner Approximation Algorithm
Wei Lian, WangMeng Zuo, Lei Zhang
Aligning partially overlapping point sets where there is no prior information about the value of the transformation is a challenging problem in computer vision. To achieve this goa…
Flexible Image Denoising with Multi-layer Conditional Feature Modulation
Jiazhi Du, Xin Qiao, Zifei Yan +2
For flexible non-blind image denoising, existing deep networks usually take both noisy image and noise level map as the input to handle various noise levels with a single model. Ho…
Cross-Scale Internal Graph Neural Network for Image Super-Resolution
Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo +1
Non-local self-similarity in natural images has been well studied as an effective prior in image restoration. However, for single image super-resolution (SISR), most existing deep…
Learning Context-Based Non-local Entropy Modeling for Image Compression
Mu Li, Kai Zhang, Wangmeng Zuo +2
The entropy of the codes usually serves as the rate loss in the recent learned lossy image compression methods. Precise estimation of the probabilistic distribution of the codes pl…
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte +87
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new versi…
Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation
Zhaohui Zheng, Ping Wang, Dongwei Ren +4
Deep learning-based object detection and instance segmentation have achieved unprecedented progress. In this paper, we propose Complete-IoU (CIoU) loss and Cluster-NMS for enhancin…
Deep Adaptive Inference Networks for Single Image Super-Resolution
Ming Liu, Zhilu Zhang, Liya Hou +2
Recent years have witnessed tremendous progress in single image super-resolution (SISR) owing to the deployment of deep convolutional neural networks (CNNs). For most existing meth…
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective
Qilong Wang, Li Zhang, Banggu Wu +4
Recent works have demonstrated that global covariance pooling (GCP) has the ability to improve performance of deep convolutional neural networks (CNNs) on visual classification tas…
Towards Photo-Realistic Virtual Try-On by Adaptively GeneratingPreserving Image Content
Han Yang, Ruimao Zhang, Xiaobao Guo +3
Image visual try-on aims at transferring a target clothing image onto a reference person, and has become a hot topic in recent years. Prior arts usually focus on preserving the cha…