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|Session Name:||Production-Level Facial Performance Capture Using Deep Convolutional Neural Networks|
|Company Name(s):||Remedy Entertainment|
|Track / Format:||Programming|
|Overview:||In this presentation Antti Herva, Lead Character Technical Artist at Remedy Entertainment will present a machine learning solution that enables cost efficient creation of large amounts of high quality facial animation for digital doubles in games. To this end, Remedy Entertainment, Nvidia and the University of Southern California's recently researched "Production-Level Facial Performance Capture Using Deep Convolutional Neural Networks" was published as part of the Symposium on Computer Animation in 2017. Topics covered in this session include recording a facial animation dataset for an actor, setting up a deep learning project, preprocessing the data, training a deep convolutional neural network, evaluating the results, a summary of the findings and a discussion on potential future work.|