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Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic
  Super-resolution

Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution

5 November 2021
Andreas Lugmayr
Martin Danelljan
F. I. F. Richard Yu
Luc Van Gool
Radu Timofte
ArXivPDFHTML

Papers citing "Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution"

3 / 3 papers shown
Title
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and
  Results
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr
Martin Danelljan
Radu Timofte
Namhyuk Ahn
Dongwoon Bai
...
Tongtong Zhao
Yuanbo Zhou
Haijie Zhuo
Ziyao Zong
Xueyi Zou
SupR
69
170
0
05 May 2020
Unsupervised Learning for Real-World Super-Resolution
Unsupervised Learning for Real-World Super-Resolution
Andreas Lugmayr
Martin Danelljan
Radu Timofte
SSL
SupR
127
167
0
20 Sep 2019
Image-to-Image Translation with Conditional Adversarial Networks
Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola
Jun-Yan Zhu
Tinghui Zhou
Alexei A. Efros
SSeg
212
19,387
0
21 Nov 2016
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