NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results
ETH Zurich · University of California, Merced · +25 more institutions
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.
Citation impact
- FWCI
- 53.79
- Percentile
- 100%
- References
- 52
Authors
77Topics & keywords
- Bicubic interpolation
- Kernel (algebra)
- Computer science
- Artificial intelligence
- Focus (optics)
- Image resolution
- Computer vision
- Image (mathematics)