Total Selfie: Generating Full-Body Selfies

Fuente: arXiv
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Autori principali: Chen, Bowei, Curless, Brian, Kemelmacher-Shlizerman, Ira, Seitz, Steven M.
Natura: Preprint
Pubblicazione: 2023
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author Chen, Bowei
Curless, Brian
Kemelmacher-Shlizerman, Ira
Seitz, Steven M.
author_facet Chen, Bowei
Curless, Brian
Kemelmacher-Shlizerman, Ira
Seitz, Steven M.
contents We present a method to generate full-body selfies from photographs originally taken at arms length. Because self-captured photos are typically taken close up, they have limited field of view and exaggerated perspective that distorts facial shapes. We instead seek to generate the photo some one else would take of you from a few feet away. Our approach takes as input four selfies of your face and body, a background image, and generates a full-body selfie in a desired target pose. We introduce a novel diffusion-based approach to combine all of this information into high-quality, well-composed photos of you with the desired pose and background.
format Preprint
id arxiv_https___arxiv_org_abs_2308_14740
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Total Selfie: Generating Full-Body Selfies
Chen, Bowei
Curless, Brian
Kemelmacher-Shlizerman, Ira
Seitz, Steven M.
Computer Vision and Pattern Recognition
Graphics
Machine Learning
We present a method to generate full-body selfies from photographs originally taken at arms length. Because self-captured photos are typically taken close up, they have limited field of view and exaggerated perspective that distorts facial shapes. We instead seek to generate the photo some one else would take of you from a few feet away. Our approach takes as input four selfies of your face and body, a background image, and generates a full-body selfie in a desired target pose. We introduce a novel diffusion-based approach to combine all of this information into high-quality, well-composed photos of you with the desired pose and background.
title Total Selfie: Generating Full-Body Selfies
topic Computer Vision and Pattern Recognition
Graphics
Machine Learning
url https://arxiv.org/abs/2308.14740