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2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2017)
Honolulu, Hawaii, USA
July 21, 2017 to July 26, 2017
ISSN: 2160-7516
ISBN: 978-1-5386-0733-6
pp: 1122-1131
ABSTRACT
This paper introduces a novel large dataset for example-based single image super-resolution and studies the state-of-the-art as emerged from the NTIRE 2017 challenge. The challenge is the first challenge of its kind, with 6 competitions, hundreds of participants and tens of proposed solutions. Our newly collected DIVerse 2K resolution image dataset (DIV2K) was employed by the challenge. In our study we compare the solutions from the challenge to a set of representative methods from the literature and evaluate them using diverse measures on our proposed DIV2K dataset. Moreover, we conduct a number of experiments and draw conclusions on several topics of interest. We conclude that the NTIRE 2017 challenge pushes the state-of-the-art in single-image super-resolution, reaching the best results to date on the popular Set5, Set14, B100, Urban100 datasets and on our newly proposed DIV2K.
INDEX TERMS
Image resolution, Atmospheric measurements, Particle measurements, Image quality, Image restoration, Degradation, Agriculture
CITATION

E. Agustsson and R. Timofte, "NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study," 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, Hawaii, USA, 2017, pp. 1122-1131.
doi:10.1109/CVPRW.2017.150
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