English

ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial Network

Image and Video Processing 2020-07-16 v2 Machine Learning

Abstract

Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) is a perceptual-driven approach for single image super resolution that is able to produce photorealistic images. Despite the visual quality of these generated images, there is still room for improvement. In this fashion, the model is extended to further improve the perceptual quality of the images. We have designed a novel block to replace the one used by the original ESRGAN. Moreover, we introduce noise inputs to the generator network in order to exploit stochastic variation. The resulting images present more realistic textures. The code is available at https://github.com/ncarraz/ESRGANplus .

Keywords

Cite

@article{arxiv.2001.08073,
  title  = {ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial Network},
  author = {Nathanaël Carraz Rakotonirina and Andry Rasoanaivo},
  journal= {arXiv preprint arXiv:2001.08073},
  year   = {2020}
}

Comments

ICASSP 2020

R2 v1 2026-06-23T13:17:46.398Z