Marshall, Carl S.Vembar, Deepak S.Ganguly, SujoyGuinier, FlorentHahmann, StefaniePatow, Gustavo A.2022-04-222022-04-222022978-3-03868-172-41017-4656https://doi.org/10.2312/egt.20221059https://diglib.eg.org:443/handle/10.2312/egt20221059Applying machine learning to improve graphics rendering or asset pipelines is challenging. Practicalities such as proprietary datasets, network retraining, and deployment issues make it difficult to translate published research into deployed solutions. In this course, industry practitioners at the forefront of this interdisciplinary field discuss and outline potential solutions.Attribution 4.0 International LicensePractical Machine Learning for Rendering: From Research to Deployment10.2312/egt.20221059