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NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

Authors :
Timofte, R
Agustsson, E
Gool, LV
Yang, MH
Zhang, L
Lim, B
Son, S
Kim, H
Nah, S
Lee, KM
Wang, X
Tian, Y
Yu, K
Zhang, Y
Wu, S
Dong, C
Lin, L
Qiao, Y
Loy, CC
Bae, W
Yoo, J
Han, Y
Ye, JC
Choi, JS
Kim, M
Fan, Y
Yu, J
Han, W
Liu, D
Yu, H
Wang, Z
Shi, H
Huang, TS
Chen, Y
Zhang, K
Zuo, W
Tang, Z
Luo, L
Li, S
Fu, M
Cao, L
Heng, W
Bui, G
Le, T
Duan, Y
Tao, D
Wang, R
Lin, X
Pang, J
Xu, J
Zhao, Y
Xu, X
Pan, J
Sun, D
Song, X
Dai, Y
Qin, X
Huynh, XP
Guo, T
Mousavi, HS
Vu, TH
Monga, V
Cruz, C
Egiazarian, K
Katkovnik, V
Mehta, R
Jain, AK
Agarwalla, A
Praveen, CVS
Zhou, R
Wen, H
Zhu, C
Xia, Z
Guo, Q
Publication Year :
2017

Abstract

© 2017 IEEE. This paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results. A new DIVerse 2K resolution image dataset (DIV2K) was employed. The challenge had 6 competitions divided into 2 tracks with 3 magnification factors each. Track 1 employed the standard bicubic downscaling setup, while Track 2 had unknown downscaling operators (blur kernel and decimation) but learnable through low and high res train images. Each competition had b∼100 registered participants and 20 teams competed in the final testing phase. They gauge the state-of-the-art in single image super-resolution.

Details

Database :
OpenAIRE
Accession number :
edsair.od.......363..a383a2546b011d1b9b9d362f568de4c2