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AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results

Part of the Lecture Notes in Computer Science book series (LNIP,volume 12537)

Abstract

This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor \(\times \)4 based on a set of prior examples of low and corresponding high resolution images. The goal is to devise a network that reduces one or several aspects such as runtime, parameter count, FLOPs, activations, and memory consumption while at least maintaining PSNR of MSRResNet. The track had 150 registered participants, and 25 teams submitted the final results. They gauge the state-of-the-art in efficient single image super-resolution.

K. Zhang, M. Danelljan, Y. Li and R. Timofte were the challenge organizers, while the other authors participated in the challenge.

Appendix A contains the authors’ teams and affiliations. AIM webpage: https://data.vision.ee.ethz.ch/cvl/aim20/

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Acknowledgements

We thank the AIM 2020 sponsors: HUAWEI, MediaTek, Google, NVIDIA, Qualcomm, and Computer Vision Lab (CVL) ETH Zurich.

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Authors and Affiliations

Authors

Corresponding author

Correspondence to Kai Zhang .

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Editors and Affiliations

A Teams and Affiliations

A Teams and Affiliations

AIM2020 Team

Title: AIM 2020 Efficient Super-Resolution Challenge

Members:

Kai Zhang (mailto:kai.zhang@vision.ee.ethz.ch),

Martin Danelljan (martin.danelljan@vision.ee.ethz.ch),

Yawei Li (yawei.li@vision.ee.ethz.ch),

Radu Timofte (radu.timofte@vision.ee.ethz.ch)

Affiliations:

Computer Vision Lab, ETH Zurich, Switzerland

NJU_MCG

Title: Residual Feature Distillation Network (RFDN)

Members: Jie Liu

(jieliu@smail.nju.edu.cn), Jie Tang, Gangshan Wu

Affiliation:

State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China

AiRiA_CG

Title: Faster Information Multi-distillation Network via Asymmetric Convolution

Members: Yu Zhu

(zhuyu.cv@gmail.com), Xiangyu He, Wenjie Xu, Chenghua Li, Cong Leng, Jian Cheng

Affiliation:

Nanjing Artificial Intelligence Chip Research, Institute of Automation, Chinese Academy of Sciences (AiRiA); MAICRO

UESTC-MediaLab

Title: Efficient Super-Resolution with Gradually Kernel Dilution

Members: Guangyang Wu\(^{1}\)

(mulns@outlook.com), Wenyi Wang\(^{1}\), Xiaohong Liu\(^{2}\)

Affiliation:

\(^{1}\) University of Electronic Science and Technology of China

\(^{2}\) McMaster University

XPixel

Title: Efficient Image Super-Resolution using Pixel Attention

Members: Hengyuan Zhao

(hy.zhao1@siat.ac.cn), Xiangtao Kong, Jingwen He,Yu Qiao, Chao Dong

Affiliation:

Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

HaiYun

Title: Lightweight Image Super-resolution with Lattice Block

Members: Xiaotong Luo

(xiaotluo@qq.com), Liang Chen, Jiangtao Zhang

Affiliation:

Xiamen University, China

IPCV_IITM

Title: Lightweight Attentive Residual Network for Image Super-Resolution

Members: Maitreya Suin

(maitreyasuin21@gmail.com), Kuldeep Purohit, A. N. Rajagopalan

Affiliation:

Indian Institute of Technology Madras, India

404NotFound

Title: GCSR

Members: Xiaochuan Li

(1182784700@qq.com)

Affiliation:

Nanjing University of Aeronautics and Astronautics, Nanjing, China

MDISL-lab

Title: PFSNet: Partial Features Sharing for More Efficient Super-Resolution

Members: Zhiqiang Lang

(2015303107lang@mail.nwpu.edu.cn), Jiangtao Nie, Wei Wei, Lei Zhang

Affiliation:

School of Computer Science, Northwestern Polytechnical University, China

MLVC

Title: Multi Attention Feature Fusion Super-Resolution Network

Members: Abdul Muqeet\(^{1}\)

(amuqeet@khu.ac.kr), Jiwon Hwang\(^{1}\), Subin Yang\(^{1}\), JungHeum Kang\(^{1}\), Sungho Bae\(^{1}\), Yongwoo Kim\(^{2}\)

Affiliation:

\(^{1}\) Kyung Hee University, Republic of Korea

\(^{2}\) Sang Myung University, Republic of Korea

XMUlab

Title: Pixelshuffle Attention Network

Members: Liang Chen

(1806668306@qq.com), Jiangtao Zhang, Xiaotong Luo, Yanyun Qu

Affiliation:

Xianmen University

MCML-Yonsei

Title: LarvaNet: Hierarchical Super-Resolution via Internal Output and Loss

Members: Geun-Woo Jeon

(geun-woo.jeon@yonsei.ac.kr), Jun-Ho Choi, Jun-Hyuk Kim, Jong-Seok Lee

Affiliation:

Yonsei University, Republic of Korea

LMSR

Title: LMSR

Members: Steven Marty

(martyste@student.ethz.ch), Eric Marty

Affiliation:

ETH Zurich

ZJUESR2020

Title: IdleSR: Efficient Super-Resolution Network with Multi-Scale IdleBlocks

Members: Dongliang Xiong (xiongdl@zju.edu.cn)

Affiliation: Zhejiang University

SC-CVLAB

Title: Adaptive Hybrid Composition Based Super-Resolution Network via Fine-grained Channel Pruning

Members: Siang Chen

(11631032@zju.edu.cn)

Affiliation: Zhejiang University

HiImageTeam

Title: Efficient SR-Net

Members: Lin Zha\(^{1}\)

(zhalin@hisense.com), Jiande Jiang\(^{1}\), Xinbo Gao\(^{2}\), Wen Lu\(^{2}\)

Affiliation:

\(^{1}\) Qingdao Hi-image Technologies Co.,Ltd (Hisense Visual Technology Co.,Ltd.)

\(^{2}\) Xidian University

SAMSUNG_TOR_AIC

Title: Lightweight MobileNetV3 for Efficient Super-Resolution

Members: Haicheng Wang

(h.wang1@samsung.com), Vineeth Bhaskara, Alex Levinshtein, Stavros Tsogkas, Allan Jepson

Affiliation: Samsung AI Centre, Toronto

neptuneai

Title: Lightweight super resolution network with Neural Architecture Search

Members: Xiangzhen Kong

(neptune.team.ai@gmail.com)

lyl

Title: Coarse to Fine Pyramid Networks for Progressive Image Super-Resolution

Members: Tongtong Zhao\(^{1}\)

(yaopuss@126.com), Shanshan Zhao\(^{2}\)

Affiliation:

\(^{1}\) Dalian Maritime University

\(^{2}\) China Everbright Bank Co., Ltd

CET_CVLab

Title: Efficient Single Image Super-resolution using Progressive Wide Activation Net

Members: Hrishikesh P S

(hrishikeshps94@gmail.com), Densen Puthussery, Jiji C V

Affiliation:

College of Engineering, Trivandrum

wozhu

Title: FSSR

Members: Nan Nan

(2829272117@qq.com), Shuai Liu

InnoPeak_SR

Title: Shuffled Recursive Residual Network for Efficient Image Super-Resolution

Members: Jie Cai

(caijie0620@mail.com), Zibo Meng, Jiaming Ding, Chiu Man Ho

Affiliation:

InnoPeak Technology, Inc.

Summer

Title: Adaptively Multi-gradients Auxiliary Feature Learning for Efficient Super-resolution

Members: Xuehui Wang\(^{1,2}\)

(wangxh228@mail2.sysu.edu.cn), Qiong Yan\(^{1}\), Yuzhi Zhao\(^{3}\), Long Chen\(^{2}\)

Affiliation:

\(^{1}\) SenseTime Research

\(^{2}\) Sun Yat-sen University

\(^{3}\) City University of Hong Kong

Zhang9678

Title: Lightweight super-resolution network using convLSTM fusion features

Members: Jiangtao Zhang

(1328937778@qq.com),

Xiaotong Luo, Liang Chen, Yanyun Qu

Affiliation:

Xianmen University

H-ZnCa

Title: Sparse Prior-based Network for Efficient Image Super-Resolution

Members: Long Sun

(lungsuen@163.com), Wenhao Wang, Zhenbing Liu, Rushi Lan

Affiliation:

Guilin University of Electronic Technology, Guilin 541004, China.

MLP_SR

Title: A Light-weight Deep Iterative Residual Convolutional Network for Super-Resolution

Members: Rao Muhammad Umer

(engr.raoumer943@gmail.com), Christian Micheloni

Affiliation:

University of Udine, Italy

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Zhang, K. et al. (2020). AIM 2020 Challenge on Efficient 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_1

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