Human Face Modeling based on Deep Learning through Line-drawing
Date
2022Author
Kawanaka, Yuta
Sato, Syuhei
Sakurai, Kaisei
Gao, Shangce
Tang, Zheng
Metadata
Show full item recordAbstract
This paper presents a deep learning-based method for creating 3D human face models. In recent years, several sketch-based shape modeling methods have been proposed. These methods allow the user to easily model various shapes containing animal, building, vehicle, and so on. However, a few methods have been proposed for human face models. If we can create 3D human face models via line-drawing, models of cartoon or fantasy characters can be easily created. To achieve this, we propose a sketch-based face modeling method. When a single line-drawing image is input to our system, a corresponding 3D face model are generated. Our system is based on a deep learning; many human face models and corresponding images rendered as line-drawing are prepared, and then a network is trained using these datasets. For the network, we use a previous method for reconstructing human bodies from real images, and we propose some extensions to enhance learning accuracy. Several examples are shown to demonstrate usefulness of our system.
BibTeX
@inproceedings {10.2312:pg.20221239,
booktitle = {Pacific Graphics Short Papers, Posters, and Work-in-Progress Papers},
editor = {Yang, Yin and Parakkat, Amal D. and Deng, Bailin and Noh, Seung-Tak},
title = {{Human Face Modeling based on Deep Learning through Line-drawing}},
author = {Kawanaka, Yuta and Sato, Syuhei and Sakurai, Kaisei and Gao, Shangce and Tang, Zheng},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-190-8},
DOI = {10.2312/pg.20221239}
}
booktitle = {Pacific Graphics Short Papers, Posters, and Work-in-Progress Papers},
editor = {Yang, Yin and Parakkat, Amal D. and Deng, Bailin and Noh, Seung-Tak},
title = {{Human Face Modeling based on Deep Learning through Line-drawing}},
author = {Kawanaka, Yuta and Sato, Syuhei and Sakurai, Kaisei and Gao, Shangce and Tang, Zheng},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-190-8},
DOI = {10.2312/pg.20221239}
}