https://github.com/interdigitalinc/stylebasedfilmgrain

Official implementation for paper : Style-based film grain analysis and synthesis
https://github.com/interdigitalinc/stylebasedfilmgrain

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Official implementation for paper : Style-based film grain analysis and synthesis

• Host: GitHub
• URL: https://github.com/interdigitalinc/stylebasedfilmgrain
• Owner: InterDigitalInc
• Created: 2023-04-13T15:58:41.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-04-15T01:36:33.000Z (over 1 year ago)
• Last Synced: 2024-04-24T12:48:38.996Z (9 months ago)
• Size: 3.91 KB
• Stars: 4
• Watchers: 2
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
### Style-based film grain analysis and synthesis

This repository implements the work published in:

Zoubida Ameur, Claire-Hélène Demarty, Olivier Le Meur, Daniel Ménard and Edouard François. "Style-based film grain analysis and synthesis." ACM Multimedia Systems (2023).

## Abstract

Film grain which used to be a by-product of the chemical processing in the analog film stock, is a desirable feature in the era of digital

cameras. Besides participating to the artistic intent during content creation, film grain has also interesting properties in the video

compression chain such as its ability to mask compression artifacts. In this paper, we use a deep learning-based framework for film grain

analysis, generation and synthesis. Our framework consists of three modules: a style encoder performing film grain style analysis, a

mapping network responsible for film grain style generation, and a synthesis network that generates and blends a specific grain

style to a given content in a content-adaptive manner. All modules are trained jointly, thanks to dedicated loss functions, on a large

and diverse dataset of pairs of grain-free and grainy images, made publicly available to the community. Quantitative and qualitative

evaluations show that fidelity to the reference grain, diversity of grain styles as well as a perceptually pleasant grain synthesis are

achieved, demonstrating that each module outperforms the state-of-the-art in the task it was designed for.

### This repository is currently under construction.