Generative Models for Pose Transfer

We investigate nearest neighbor and generative models for transferring pose between persons. We take in a video of one person performing a sequence of actions and attempt to generate a video of another person performing the same actions. Our generative model (pix2pix) outperforms k-NN at both genera...

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Bibliographic Details
Main Authors Chao, Patrick, Li, Alexander, Swamy, Gokul
Format Journal Article
LanguageEnglish
Published 23.06.2018
Subjects
Computer Science - Graphics
Computer Science - Learning
Statistics - Machine Learning
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Summary:We investigate nearest neighbor and generative models for transferring pose between persons. We take in a video of one person performing a sequence of actions and attempt to generate a video of another person performing the same actions. Our generative model (pix2pix) outperforms k-NN at both generating corresponding frames and generalizing outside the demonstrated action set. Our most salient contribution is determining a pipeline (pose detection, face detection, k-NN based pairing) that is effective at perform-ing the desired task. We also detail several iterative improvements and failure modes.
DOI:10.48550/arxiv.1806.09070