Autor:	Kim, Byung-Hak, Ganapathi, Varun
Rok vydání:	2019
Předmět:	Computer Science - Machine Learning Computer Science - Computer Vision and Pattern Recognition Electrical Engineering and Systems Science - Audio and Speech Processing Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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].
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1907.02253 Zobrazit plný text záznamu View this record from Arxiv