ECCV_2018

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Super resolution

To learn image super-resolution, use a GAN to learn how to do image degradation first
Adrian Bulat*, University of Nottingham; Jing Yang, University of Nottingham; Georgios Tzimiropoulos, University of Nottingham

CrossNet: An End-to-end Reference-based Super Resolution Network using Cross-scale Warping
Haitian Zheng, HKUST; Mengqi Ji, HKUST; Haoqian Wang, Tsinghua University; Yebin Liu*, Tsinghua University; Lu Fang, Tsinghua University

Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Yulun Zhang*, Northeastern University; Kunpeng Li, Northeastern University; kai li, northeastern university; Lichen Wang, Northeastern University; Bineng Zhong, Huaqiao University; YUN FU, Northeastern University

Multi-scale Residual Network for Image Super-Resolution
Juncheng Li, East China Normal University; Faming Fang*, East China Normal University; Kangfu Mei, Jiangxi Normal University; Guixu Zhang, East China Normal University

Face Super-resolution Guided by Facial Component Heatmaps
Xin Yu*, Australian National University; Basura Fernando, Australian National University; Bernard Ghanem, KAUST; Fatih Porikli, ANU; RICHARD HARTLEY, Australian National University, Australia

Fast, Accurate, and, Lightweight Super-Resolution with Cascading Residual Network
Namhyuk Ahn, Ajou University; Byungkon Kang, Ajou University; Kyung-Ah Sohn*, Ajou University

SRFeat: Single Image Super Resolution with Feature Discrimination
Seong-Jin Park*, POSTECH; Hyeongseok Son, POSTECH; Sunghyun Cho, DGIST; Ki-Sang Hong, POSTECH; Seungyong Lee, POSTECH

Super-Resolution and Sparse View CT Reconstruction
Guangming Zang, KAUST; Ramzi Idoughi, KAUST; Mohamed Aly, KAUST; Peter Wonka, KAUST; Wolfgang Heidrich*, KAUST

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Deblur

Burst Image Deblurring Using Permutation Invariant Convolutional Neural Networks
Miika Aittala*, MIT; Fredo Durand, MIT

Deblurring Natural Image Using Super-Gaussian Fields
Yuhang Liu, Wuhan University; Wenyong Dong*, Wuhan University; Dong Gong, Northwestern Polytechnical University & The University of Adelaide; Lei Zhang, The unversity of Adelaide; Qinfeng Shi, University of Adelaide

Unsupervised Class-Specific Deblurring
Nimisha T M*, Indian Institute of Technology Madras; Sunil Kumar, Indian Institute of Technology Madras; Rajagopalan Ambasamudram, Indian Institute of Technology Madras

Learning Data Terms for Image Deblurring
Jiangxin Dong*, Dalian University of Technology; Jinshan Pan, Dalian University of Technology; Deqing Sun, NVIDIA; Zhixun Su, Dalian University of Technology; Ming-Hsuan Yang, University of California at Merced

Joint Blind Motion Deblurring and Depth Estimation of Light Field
Dongwoo Lee, Seoul Ntional University; Haesol Park, Seoul National University; In Kyu Park, Inha University; Kyoung Mu Lee*, Seoul National University

Denoise

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Restoration

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Spatio-temporal Transformer Network for Video Restoration
Tae Hyun Kim*, Max Planck Institute for Intelligent Systems; Mehdi S. M. Sajjadi, Max Planck Institute for Intelligent Systems; Michael Hirsch, Max Planck Institut for Intelligent Systems ; Bernhard Schölkopf, Max Planck Institute for Intelligent Systems

Learning Warped Guidance for Blind Face Restoration
Xiaoming Li, Harbin Institute of Technology; Ming Liu, Harbin Institute of Technology; Yuting Ye, Harbin Institute of Technology; Wangmeng Zuo*, Harbin Institute of Technology, China; Liang Lin, Sun Yat-sen University; Ruigang Yang, University of Kentucky, USA

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Inpainting

Contextual Based Image Inpainting: Infer, Match and Translate
Yuhang Song*, USC; Chao Yang, University of Southern California; Zhe Lin, Adobe Research; Xiaofeng Liu, Carnegie Mellon University; Hao Li, Pinscreen/University of Southern California/USC ICT; Qin Huang, University of Southern California; C.-C. Jay Kuo, USC

Image Inpainting for Irregular Holes Using Partial Convolutions
Guilin Liu*, NVIDIA; Fitsum Reda, NVIDIA; Kevin Shih, NVIDIA; Ting-Chun Wang, NVIDIA; Andrew Tao, NVIDIA; Bryan Catanzaro, NVIDIA

Shift-Net: Image Inpainting via Deep Feature Rearrangement
Zhaoyi Yan, Harbin Institute of Technology; Xiaoming Li, Harbin Institute of Technology; Mu LI, The Hong Kong Polytechnic University; Wangmeng Zuo*, Harbin Institute of Technology, China; Shiguang Shan, Chinese Academy of Sciences

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Dehaze

Proximal Dehaze-Net: A Prior Learning-Based Deep Network for Single Image Dehazing
Dong Yang, Xi'an Jiaotong University; JIAN SUN*, Xi'an Jiaotong University

Does Haze Removal Help Image Classification?
Yanting Pei*, Beijing Jiaotong University; Yaping Huang, Beijing Jiaotong University; Qi Zou, Beijing Jiaotong University; Yuhang Lu, University of South Carolina; Song Wang, University of South Carolina

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Deraining

Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining
Xia Li*, Peking University Shenzhen Graduate School; Jianlong Wu, Peking University; Zhouchen Lin, Peking University; Hong Liu, Peking University Shenzhen Graduate School; Hongbin Zha, Peking University, China

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Enhance

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ICCV _2017

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Super resolution

Anchored Regression Networks Applied to Age Estimation and Super Resolution
Eirikur Agustsson, Radu Timofte, Luc Van Gool

Wavelet-SRNet: A Wavelet-Based CNN for Multi-Scale Face Super Resolution
Huaibo Huang, Ran He, Zhenan Sun, Tieniu Tan

Robust Video Super-Resolution With Learned Temporal Dynamics
Ding Liu, Zhaowen Wang, Yuchen Fan, Xianming Liu, Zhangyang Wang, Shiyu Chang, Thomas Huang

Detail-Revealing Deep Video Super-Resolution
Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, Jiaya Jia

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis
Mehdi S. M. Sajjadi, Bernhard Scholkopf, Michael Hirsch

Joint Estimation of Camera Pose, Depth, Deblurring, and Super-Resolution From a Blurred Image Sequence
Haesol Park, Kyoung Mu Lee

Image Super-Resolution Using Dense Skip Connections
Tong Tong, Gen Li, Xiejie Liu, Qinquan Gao

Pixel Recursive Super Resolution
Ryan Dahl, Mohammad Norouzi, Jonathon Shlens

Temporal Shape Super-Resolution by Intra-Frame Motion Encoding Using High-Fps Structured Light
Yuki Shiba, Satoshi Ono, Ryo Furukawa, Shinsaku Hiura, Hiroshi Kawasaki

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deblur

Learning Blind Motion Deblurring
Patrick Wieschollek, Michael Hirsch, Bernhard Scholkopf, Hendrik P. A. Lensch

Learning Discriminative Data Fitting Functions for Blind Image Deblurring
Jinshan Pan, Jiangxin Dong, Yu-Wing Tai, Zhixun Su, Ming-Hsuan Yang

Video Deblurring via Semantic Segmentation and Pixel-Wise Non-Linear Kernel
Wenqi Ren, Jinshan Pan, Xiaochun Cao, Ming-Hsuan Yang

Self-Paced Kernel Estimation for Robust Blind Image Deblurring
Dong Gong, Mingkui Tan, Yanning Zhang, Anton van den Hengel, Qinfeng Shi

Blind Image Deblurring With Outlier Handling
Jiangxin Dong, Jinshan Pan, Zhixun Su, Ming-Hsuan Yang

Non-Uniform Blind Deblurring by Reblurring
Yuval Bahat, Netalee Efrat, Michal Irani

Going Unconstrained With Rolling Shutter Deblurring
Mahesh Mohan M. R., A. N. Rajagopalan, Gunasekaran Seetharaman

Online Video Deblurring via Dynamic Temporal Blending Network
Tae Hyun Kim, Kyoung Mu Lee, Bernhard Scholkopf, Michael Hirsch

Blur-Invariant Deep Learning for Blind-Deblurring
T. M. Nimisha, Akash Kumar Singh, A. N. Rajagopalan

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Denoise

Transformed Low-Rank Model for Line Pattern Noise Removal
Yi Chang, Luxin Yan, Sheng Zhong

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Restoration

On-Demand Learning for Deep Image Restoration
Ruohan Gao, Kristen Grauman

MemNet: A Persistent Memory Network for Image Restoration
Ying Tai, Jian Yang, Xiaoming Liu, Chunyan Xu

ECCV_2016

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Super resolution

Accelerating the Super-Resolution Convolutional Neural Network
CHAO DONG, The Chinese University of HK; Chen-Change Loy, the Chinese University of Hong Kong; Xiaoou Tang, Chinese University of Hong Kong

Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Justin Johnson, Stanford University; Alexandre Alahi, Stanford University; Fei-Fei Li, Stanford University

Hierarchical Beta Process with Gaussian Process prior for Hyperspectral Image Super Resolution
Naveed Akhtar, Uni. of Western Australia; Faisal Shafait, ; Ajmal Mian, UWA

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Deblur

Stereo Video Deblurring
Anita Sellent, Technische Universit?t Darmstadt, Technische Universit?t Dresden; Carsten Rother, ; Stefan Roth, TU Darmstadt

A Neural Approach to Blind Motion Deblurring
Ayan Chakrabarti, TTI-Chicago

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ICCV_2015

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Super resolution

Naive Bayes Super-Resolution Forest
Jordi Salvador, Eduardo Pérez-Pellitero

Deep Networks for Image Super-Resolution With Sparse Prior
Zhaowen Wang, Ding Liu, Jianchao Yang, Wei Han, Thomas Huang

Learning Parametric Distributions for Image Super-Resolution: Where Patch Matching Meets Sparse Coding
Yongbo Li, Weisheng Dong, Guangming Shi, Xuemei Xie

Variational Depth Superresolution Using Example-Based Edge Representations
David Ferstl, Matthias Rüther, Horst Bischof

Conditioned Regression Models for Non-Blind Single Image Super-Resolution
Gernot Riegler, Samuel Schulter, Matthias Rüther, Horst Bischof

Video Super-Resolution via Deep Draft-Ensemble Learning
Renjie Liao, Xin Tao, Ruiyu Li, Ziyang Ma, Jiaya Jia

Rolling Shutter Super-Resolution
Abhijith Punnappurath, Vijay Rengarajan, A.N. Rajagopalan

Convolutional Sparse Coding for Image Super-Resolution
Shuhang Gu, Wangmeng Zuo, Qi Xie, Deyu Meng, Xiangchu Feng, Lei Zhang

Hyperspectral Super-Resolution by Coupled Spectral Unmixing
Charis Lanaras, Emmanuel Baltsavias, Konrad Schindler

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Deblur

Class-Specific Image Deblurring
Saeed Anwar, Cong Phuoc Huynh, Fatih Porikli

Complementary Sets of Shutter Sequences for Motion Deblurring
Hae-Gon Jeon, Joon-Young Lee, Yudeog Han, Seon Joo Kim, In So Kweon

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DeNoise

An Efficient Statistical Method for Image Noise Level Estimation
Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng

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Restoration

Conformal and Low-Rank Sparse Representation for Image Restoration
Jianwei Li, Xiaowu Chen, Dongqing Zou, Bo Gao, Wei Teng

Improving Image Restoration With Soft-Rounding
Xing Mei, Honggang Qi, Bao-Gang Hu, Siwei Lyu

Video Restoration Against Yin-Yang Phasing
Xiaolin Wu, Zhenhao Li, Xiaowei Deng