Kawanaka, YutaSato, SyuheiSakurai, KaiseiGao, ShangceTang, ZhengYang, YinParakkat, Amal D.Deng, BailinNoh, Seung-Tak2022-10-042022-10-042022978-3-03868-190-8https://doi.org/10.2312/pg.20221239https://diglib.eg.org:443/handle/10.2312/pg20221239This 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.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → Mesh modelsComputing methodologies → Mesh models10.2312/pg.2022123913-142 pages