The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report
arxiv(2024)
摘要
This paper provides a comprehensive review of the NTIRE 2024 challenge,
focusing on efficient single-image super-resolution (ESR) solutions and their
outcomes. The task of this challenge is to super-resolve an input image with a
magnification factor of x4 based on pairs of low and corresponding
high-resolution images. The primary objective is to develop networks that
optimize various aspects such as runtime, parameters, and FLOPs, while still
maintaining a peak signal-to-noise ratio (PSNR) of approximately 26.90 dB on
the DIV2K_LSDIR_valid dataset and 26.99 dB on the DIV2K_LSDIR_test dataset. In
addition, this challenge has 4 tracks including the main track (overall
performance), sub-track 1 (runtime), sub-track 2 (FLOPs), and sub-track 3
(parameters). In the main track, all three metrics (ie runtime, FLOPs, and
parameter count) were considered. The ranking of the main track is calculated
based on a weighted sum-up of the scores of all other sub-tracks. In sub-track
1, the practical runtime performance of the submissions was evaluated, and the
corresponding score was used to determine the ranking. In sub-track 2, the
number of FLOPs was considered. The score calculated based on the corresponding
FLOPs was used to determine the ranking. In sub-track 3, the number of
parameters was considered. The score calculated based on the corresponding
parameters was used to determine the ranking. RLFN is set as the baseline for
efficiency measurement. The challenge had 262 registered participants, and 34
teams made valid submissions. They gauge the state-of-the-art in efficient
single-image super-resolution. To facilitate the reproducibility of the
challenge and enable other researchers to build upon these findings, the code
and the pre-trained model of validated solutions are made publicly available at
https://github.com/Amazingren/NTIRE2024_ESR/.
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