Current methods for body shape estimation either lack detail or require many images. They are usually architecturally complex and computationally expensive. We propose FACSIMILE (FAX), a method that estimates a detailed body from a single photo, lowering the bar for creating virtual representations of humans. Our approach is easy to implement and fast to execute, making it easily deployable. FAX uses an image-translation network which recovers geometry at the original resolution of the image. Counterintuitively, the main loss which drives FAX is on per-pixel surface normals instead of per-pixel depth, making it possible to estimate detailed body geometry without any depth supervision. We evaluate our approach both qualitatively and quantitatively, and compare with a state-of-the-art method.
Cite
@article{arxiv.1909.00883,
title = {FACSIMILE: Fast and Accurate Scans From an Image in Less Than a Second},
author = {David Smith and Matthew Loper and Xiaochen Hu and Paris Mavroidis and Javier Romero},
journal= {arXiv preprint arXiv:1909.00883},
year = {2019}
}