Abstract
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 challenge involves three tracks to super-resolve an input image for \(\times \)2, \(\times \)3 and \(\times \)4 scaling factors, respectively. The goal is to attract more attention to realistic image degradation for the SR task, which is much more complicated and challenging, and contributes to real-world image super-resolution applications. 452 participants were registered for three tracks in total, and 24 teams submitted their results. They gauge the state-of-the-art approaches for real image SR in terms of PSNR and SSIM.
(P. Wei, H. Lu, R. Timofte, L. Lin, W. Zuo—Challenge organizers and the other others participated in the challenge. Appendix
contains the authors’s teams and affiliations. AIM webpage: https://data.vision.ee.ethz.ch/cvl/aim20/)
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Notes
- 1.
The dataset is publicly available at https://github.com/xiezw5/Component-Divide-and-Conquer-for-Real-World-Image-Super-Resolution.
- 2.
- 3.
The code is publicly available at https://github.com/swz30/MIRNet.
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Acknowledgements
We thank the AIM 2020 sponsors: Huawei, MediaTek, NVIDIA, Qualcomm AI Research, Google and Computer Vision Lab (CVL) ETH Zurich.
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Editors and Affiliations
A. Teams and Affiliations
A. Teams and Affiliations
AIM2020 team
Title: AIM 2020 Challenge on Real Image Super-Resolution
Members:
Pengxu Wei\(^1\) (weipx3@mail.sysu.edu.cn),
Hannan Lu\(^2\) (hannanlu@hit.edu.cn),
Radu Timofte\(^3\) (radu.timofte@vision.ee.ethz.ch),
Liang Lin\(^1\) (linliang@ieee.org),
Wangmeng Zuo\(^2\) (cswmzuo@gmail.com)
Affiliations:
\(^1\) Sun Yat-sen University, China
\(^2\) Harbin Institute of Technology University, China
\(^3\) Computer Vision Lab, ETH Zurich, Switzerland
Baidu
Title: Real Image Super Resolution via Heterogeneous Model Ensemble using GP-NAS
Members: Zhihong Pan\(^1\) (zhihongpan@baidu.com), Baopu Li\(^1\) Teng Xi\(^2\), Yanwen Fan\(^2\), Gang Zhang\(^2\), Jingtuo Liu\(^2\), Junyu Han\(^2\), Errui Ding\(^2\)
Affiliation:
\(^1\) Baidu Research (USA)
\(^2\) Department of Computer Vision Technology (VIS), Baidu Incorportation
CETC-CSKT
Title: Adaptive dense connection super resolution reconstruction
Members: Tangxin Xie (xxh96@outlook.com), Yi Shen, Jialiang Zhang, Yu Jia, Liang Cao, Yan Zou
Affiliation: China Electronic Technology Cyber Security Co., Ltd.
OPPO_CAMERA
Title: Self-Calibrated Attention Neural Network for Real-World Super Resolution
Members: Kaihua Cheng (chengkaihua@oppo.com), Chenhuan Wu
Affiliation: Guangdong OPPO Mobile Telecommunications Corp., Ltd.
ALONG
Title: Dual Path Network with High Frequency Guided for Real World Image Super-Resolution
Members: Yue Lin (gzlinyue@corp.netease.com), Cen Liu, Yunbo Peng
Affiliation: NetEase Games AI Lab
Noah_TerminalVision
Title: Super Resolution with weakly-paired data using an Adaptive Robust Loss
Members: Xueyi Zou (zouxueyi@huawei.com),
Affiliation: Noah’s Ark Lab, Huawei
DeepBlueAI
Title: A solution based on RCAN
Members: Zhipeng Luo, Yuehan Yao (yaoyh@deepblueai.com), Zhenyu Xu
Affiliation: DeepBlue Technology (Shanghai) Co., Ltd
TeamInception
Title: Learning Enriched Features for Real Image Restoration and Enhancement
Members: Syed Waqas Zamir (waqas.zamir@inceptioniai.org), Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan
Affiliation: Inception Institute of Artificial Intelligence (IIAI)
MCML-Yonsei
Title: Multi-scale Dynamic Residual Network Using Total Variation for Real Image Super-Resolution
Members: Keon-Hee Ahn (khahn196@gmail.com), Jun-Hyuk Kim, Jun-Ho Choi, Jong-Seok Lee
Affiliation: Yonsei University
lyl
Title: Coarse to Fine Pyramid Networks for Progressive image super-resolution
Members: Tongtong Zhao (daitoutiere@gmail.com), Shanshan Zhao
Affiliation: Dalian Maritime Univerity
kailos
Title: RRDB Network with Attention mechanism using Wavelet loss for Single Image Super-Resolution
Members: Yoseob Han\(^1\) (yoseobhan@lanl.gov), Byung-Hoon Kim\(^2\), JaeHyun Baek\(^3\)
Affiliation:
\(^1\) Loa Alamos National Laboratory (LANL)
\(^2\) Korea Advanced Institute of Science and Technology (KAIST)
\(^3\) Amazon Web Services (AWS)
qwq
Title: Dual Learning for SR using Multi-Scale Network
Members: Haoning Wu, Dejia Xu Affiliation: Peking University
AiAiR
Title: OADDet: Orientation-aware Convolutions Meet Dual Path Enhancement Network
Members: Bo Zhou\(^1\) (1826356001@qq.com),
Haodong Yu\(^2\) (haodong.yu@outlook.com)
Affiliation:
\(^1\) Jiangnan University
\(^2\) Karlsruher Institut fuer Technologie
JNSR
Title: Dual Path Enhancement Network
Members: Bo Zhou (jeasonzhou1@gmail.com)
Affiliation: Jiangnan University
SrDance
Title: Training Strategy Optimization
Members: Wei Guan (missanswer@163.com), Xiaobo Li, Chen Ye
Affiliation: Tongji University
GDUT-SL
Title: Ensemble of RRDB for Image Restoration
Members: Hao Li (2111903004@mail2.gdut.edu.cn), Haoyu Zhong, Yukai Shi, Zhijing Yang, Xiaojun Yang
Affiliation: Guangdong University of Technology
MoonCloud
Title: Mixed Residual Channel Attention
Members: Haoyu Zhong (hy0421@outlook.com), Yukai Shi, Xiaojun Yang, Zhijing Yang,
Affiliation: Guangdong University of Technology,
SR-IM
Title: FAN: Frequency-aware network for image super-resolution
Members: Xin Li (lixin666@mail.ustc.edu.cn), Xin Jin, Yaojun Wu, Yingxue Pang, Sen Liu
Affiliation: University of Science and Technology of China
SR_DL
Title: ABPN++: Attention based Back Projection Network for image super-resolution
Members: Zhi-Song Liu\(^1\), Li-Wen Wang\(^2\), Chu-Tak Li\(^2\), Marie-Paule Cani\(^1\), Wan-Chi Siu\(^2\)
Affiliation:
\(^1\) LIX - Computer science laboratory at the Ecole polytechnique [Palaiseau]
\(^2\) Center of Multimedia Signal Processing, The Hong Kong Polytechnic University
Webbzhou
Title: RRDB for Real World Super-Resolution
Members:Yuanbo Zhou (webbozhou@gmail.com),
Affiliation: Fuzhou University, Fujian Province, China
MLP SR
Title: Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution
Members: Rao Muhammad Umer (engr.raoumer943@gmail.com), Christian Micheloni
Affiliation: University Of Udine, Italy
congxiaofeng
Title: RDB-P SRNet: Residual-dense block with pixel shuffle
Members: Xiaofeng Cong (1752808219@qq.com)
Affiliation: (Not provided)
RRDN_IITKGP
Title: A GAN based Residual in Residual Dense Network
Members: Rajat Gupta (rajatgba2021@email.iimcal.ac.in)
Affiliation: Indian Institute of Technology
debut_kele
Title: Self-supervised Learning for Pretext Training
Members: Kele Xu (kelele.xu@gmail.com), Hengxing Cai, Yuzhong Liu
Affiliation: National University of Defense Technology
Team-24
Title: VCBPv2 - VCycles Backprojection Upscaling Network
Members: Feras Almasri, Thomas Vandamme, Olivier Debeir
Affiliation: Universié Libre de Bruxelles, LISA department
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Wei, P. et al. (2020). AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results. In: Bartoli, A., Fusiello, A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science(), vol 12537. Springer, Cham. https://doi.org/10.1007/978-3-030-67070-2_24
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