DeepAI AI Chat
Log In Sign Up

AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results

by   Andreas Lugmayr, et al.
ETH Zurich
1, Shuefu Road, Neipu, Pingtung 91201, TAIWAN
Xidian University

This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are unavailable. For training, only one set of source input images is therefore provided in the challenge. In Track 1: Source Domain the aim is to super-resolve such images while preserving the low level image characteristics of the source input domain. In Track 2: Target Domain a set of high-quality images is also provided for training, that defines the output domain and desired quality of the super-resolved images. To allow for quantitative evaluation, the source input images in both tracks are constructed using artificial, but realistic, image degradations. The challenge is the first of its kind, aiming to advance the state-of-the-art and provide a standard benchmark for this newly emerging task. In total 7 teams competed in the final testing phase, demonstrating new and innovative solutions to the problem.


page 1

page 4


NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results

This paper reviews the NTIRE2021 challenge on burst super-resolution. Gi...

Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar

Conventional face super-resolution methods usually assume testing low-re...

Two-stage domain adapted training for better generalization in real-world image restoration and super-resolution

It is well-known that in inverse problems, end-to-end trained networks o...

AIM 2022 Challenge on Instagram Filter Removal: Methods and Results

This paper introduces the methods and the results of AIM 2022 challenge ...

NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results

In this paper, we summarize the 1st NTIRE challenge on stereo image supe...

NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results

This paper reviews the NTIRE 2020 challenge on video quality mapping (VQ...

PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report

This paper reviews the first challenge on efficient perceptual image enh...

Code Repositories


[ICCVW 2019] PyTorch implementation of DSGAN and ESRGAN-FS from the paper "Frequency Separation for Real-World Super-Resolution". This code was the winning solution of the AIM challenge on Real-World Super-Resolution at ICCV 2019

view repo