FACSIMILE: Fast and Accurate Scans from an Image in Less than a Second
Abstract
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
Text
Smith et al. "FACSIMILE: Fast and Accurate Scans from an Image in Less than a Second." Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019. doi:10.1109/ICCV.2019.00543Markdown
[Smith et al. "FACSIMILE: Fast and Accurate Scans from an Image in Less than a Second." Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019.](https://mlanthology.org/iccv/2019/smith2019iccv-facsimile/) doi:10.1109/ICCV.2019.00543BibTeX
@inproceedings{smith2019iccv-facsimile,
title = {{FACSIMILE: Fast and Accurate Scans from an Image in Less than a Second}},
author = {Smith, David and Loper, Matthew and Hu, Xiaochen and Mavroidis, Paris and Romero, Javier},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision},
year = {2019},
doi = {10.1109/ICCV.2019.00543},
url = {https://mlanthology.org/iccv/2019/smith2019iccv-facsimile/}
}