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AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and
  Results

AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results

14 September 2020
Dario Fuoli
Zhiwu Huang
Shuhang Gu
Radu Timofte
Arnau Raventos
A. Esfandiari
S. Karout
Xuan Xu
Xin Li
Xin Xiong
Jinge Wang
Pablo Navarrete Michelini
Wenhao Zhang
Dongyang Zhang
Hanwei Zhu
Dan Xia
Haoyu Chen
Jinjin Gu
Zhi-Li Zhang
Tongtong Zhao
Shanshan Zhao
Kazutoshi Akita
Norimichi Ukita
S. HrishikeshP.
Densen Puthussery
V. JijiC.
    SupR
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Papers citing "AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results"

6 / 6 papers shown
Title
Burst Super-Resolution with Diffusion Models for Improving Perceptual
  Quality
Burst Super-Resolution with Diffusion Models for Improving Perceptual Quality
Kyotaro Tokoro
Kazutoshi Akita
Norimichi Ukita
28
4
0
28 Mar 2024
Joint Learning of Blind Super-Resolution and Crack Segmentation for
  Realistic Degraded Images
Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images
Yuki Kondo
Norimichi Ukita
SupR
24
8
0
24 Feb 2023
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei
Hannan Lu
Radu Timofte
Liang Lin
W. Zuo
...
Jun-Ho Choi
Jong-Seok Lee
Feras Almasri
T. Vandamme
O. Debeir
SupR
35
41
0
25 Sep 2020
Video Super Resolution Based on Deep Learning: A Comprehensive Survey
Video Super Resolution Based on Deep Learning: A Comprehensive Survey
Hongying Liu
Zhubo Ruan
Peng Zhao
Chao Dong
Fanhua Shang
Yuanyuan Liu
Linlin Yang
Radu Timofte
SupR
31
168
0
25 Jul 2020
Generative Adversarial Networks and Perceptual Losses for Video
  Super-Resolution
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution
Alice Lucas
Santiago López-Tapia
Rafael Molina
Aggelos K. Katsaggelos
GAN
SupR
38
173
0
14 Jun 2018
Real-Time Single Image and Video Super-Resolution Using an Efficient
  Sub-Pixel Convolutional Neural Network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi
Jose Caballero
Ferenc Huszár
J. Totz
Andrew P. Aitken
Rob Bishop
Daniel Rueckert
Zehan Wang
SupR
195
5,175
0
16 Sep 2016
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