“Emulating Emulsion: A Compact Physically-Based Model for Film Colour” by Jang, Karaimer and Brown
Conference:
Type(s):
Title:
- Emulating Emulsion: A Compact Physically-Based Model for Film Colour
Session/Category Title:
- Images, Video & Computer Vision
Presenter(s)/Author(s):
Abstract:
A 30-parameter, physics-based model transforms digital images into authentically scanned film colour. Trained on a single roll of colour-positive film, it matches LUT accuracy without artefacts and exposes interpretable parameters, offering filmmakers a data-light and production-ready solution to revive and preserve classic film aesthetics.
References:
[1] Pat David. 2013. Film Emulation Presets in G’MIC/GIMP. Retrieved 16 April, 2025 from https://patdavid.net/2013/08/film-emulation-presets-in-gmic-gimp/
[2] Eastman Kodak Company. 2006. Basic Photographic Sensitometry Workbook. https://www.kodak.com/content/products-brochures/Film/Basic-Photographic-Sensitometry-Workbook.pdf Kodak Publication H-740, self-teaching guide.
[3] Seon Joo Kim, Hai Ting Lin, Zheng Lu, Sabine Susstrunk, Stephen Lin, and Michael S. Brown. 2012. A New In-Camera Imaging Model for Color Computer Vision and Its Application. IEEE Transactions on Pattern Analysis and Machine Intelligence 34, 12 (2012), 2289–2302.
[4] Zinuo Li, Xuhang Chen, Shuqiang Wang, and Chi-Man Pun. 2023. A large-scale film style dataset for learning multi-frequency driven film enhancement. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence(IJCAI ’23). International Joint Conferences on Artificial Intelligence Organization, Macao, P.R.China, Article 129, 9 pages.
[5] Ethan Tseng, Yuxuan Zhang, Lars Jebe, Xuaner Zhang, Zhihao Xia, Yifei Fan, Felix Heide, and Jiawen Chen. 2022. Neural Photo-Finishing. ACM Trans. Graph. 41, 6, Article 238 (2022), 15 pages.
