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Jumping in at the deep end: how to experiment with machine learning in post-production software

Online:27 July 2019Publication History

ABSTRACT

Recent years has seen an explosion in Machine Learning (ML) research. The challenge is now to transfer these new algorithms into the hands of artists and TD's in visual effects and animation studios, so that they can start experimenting with ML within their existing pipelines. This paper presents some of the current challenges to experimentation and deployment of ML frameworks in the post-production industry. It introduces our open-source "ML-Server" client / server system as an answer to enabling rapid prototyping, experimentation and development of ML models in post-production software. Data, code and examples for the system can be found on the GitHub repository page:

https://github.com/TheFoundryVisionmongers/nuke-ML-server

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      • Published in

        ACM Conferences cover image
        DigiPro '19: Proceedings of the 2019 Digital Production Symposium
        July 2019
        52 pages
        ISBN:9781450367998
        DOI:10.1145/3329715

        Copyright © 2019 ACM

        Publisher

        Association for Computing Machinery

        New York, NY, United States

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