@inproceedings{10.1145/3532836.3536228,
	author = {Djelouah, Abdelaziz and Wahlquist, Andrew J. and Hattori, Sally and Schroers, Christopher},
	title = {Training a Deep Remastering Model},
	year = {2022},
	isbn = {9781450393713},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	url = {https://doi.org/10.1145/3532836.3536228},
	doi = {10.1145/3532836.3536228},
	abstract = {The success of video streaming platforms has pushed studios to make available TV shows from legacy catalog, and there is an increased demand for remastering this content. Ideally, film reels are re-scanned with modern devices directly into high quality digital format. However this is not always possible as parts of the original film reels can be damaged or missing, and the content is then available in its entirety only in the broadcast version, typically NTSC. In this work, we present a deep learning solution to bring the NTSC version to the new scan quality levels, which would be otherwise impossible with existing tools.},
	booktitle = {ACM SIGGRAPH 2022 Talks},
	articleno = {20},
	numpages = {2},
	location = {Vancouver, BC, Canada},
	series = {SIGGRAPH '22}
}