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LumièreNet: Lecture Video Synthesis from Audio

Published 4 Jul 2019 in cs.LG, cs.CV, eess.AS, and stat.ML | (1907.02253v1)

Abstract: We present Lumi`ereNet, a simple, modular, and completely deep-learning based architecture that synthesizes, high quality, full-pose headshot lecture videos from instructor's new audio narration of any length. Unlike prior works, Lumi`ereNet is entirely composed of trainable neural network modules to learn mapping functions from the audio to video through (intermediate) estimated pose-based compact and abstract latent codes. Our video demos are available at [22] and [23].

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