
Super-resolution aims at increasing the resolution and
level of detail within an image. The current state of the
art in general single-image super-resolution is held
by nESRGAN+,which injects a Gaussian noise after each
residual layer at training time. In this paper, we harness
evolutionary methods to improve nESRGAN+ by optimizing the
noise injection at inference time. More precisely, we use
Diagonal CMA to optimize the injected noise according to a
novel criterion combining quality assessment and realism.
Our results are validated by the PIRM perceptual score and
a human study. Our method outperforms nESRGAN+ on several
standard super-resolution datasets. More generally, our
approach can be used to optimize any method based on noise
injection.

Tarsier: Evolving Noise Injection in Super-Resolution GANs

**Session Chair**: prof. Simone Calderara

PS T5.2: Image and Signal Processing

poster

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
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The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


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Tarsier: Evolving Noise Injection in Super-Resolution GANs

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