mlsanityData to 7 Oct 2026

FREDSR: Fourier Residual Efficient Diffusive GAN for Single Image Super Resolution

arXiv 2211.16678 ↗First posted 30 Nov 2022cs.CV eess.IVcited by 1

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Abstract (arXiv)

FREDSR is a GAN variant that aims to outperform traditional GAN models in specific tasks such as Single Image Super Resolution with extreme parameter efficiency at the cost of per-dataset generalizeability. FREDSR integrates fast Fourier transformation, residual prediction, diffusive discriminators, etc to achieve strong performance in comparisons to other models on the UHDSR4K dataset for Single Image 3x Super Resolution from 360p and 720p with only 37000 parameters. The model follows the characteristics of the given dataset, resulting in lower generalizeability but higher performance on tasks such as real time up-scaling.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 38 of its 56 references that are in the map. First posted on arXiv 30 Nov 2022.

Builds on

38 of 56 references.

References · 38

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26 more
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