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ABSTRACT
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 ∽100 registered participants and 20 teams competed in the final testing phase. They gauge the state-of-the-art in single image super-resolution.
INDEX TERMS
Image resolution, Runtime, MATLAB, Tracking, Training, Image restoration, Testing
CITATION

R. Timofte et al., "NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results," 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, Hawaii, USA, 2017, pp. 1110-1121.
doi:10.1109/CVPRW.2017.149
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