期刊
出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3203187
关键词
character animation; neural networks; mesh deformation; skinning; soft-tissue
资金
- Marie Sklukodowska-Curie Individual Fellowship [707326]
- Spanish Ministry of Economy [TIN2015-70799-R]
- Marie Curie Actions (MSCA) [707326] Funding Source: Marie Curie Actions (MSCA)
We present a novel method to enrich existing vertex-based human body models by adding soft-tissue dynamics. Our model learns to predict per-vertex 3D offsets, referred to as dynamic blendshapes, that reproduce nonlinear mesh deformation effects as a function of pose information. This enables the synthesis of realistic 3D mesh animations, including soft-tissue effects, using just skeletal motion. At the core of our method there is a neural network regressor trained on high-quality 4D scans from which we extract pose, shape and soft-tissue information. Our regressor uses a novel nonlinear subspace, which we build using an autoencoder, to efficiently compact soft-tissue dynamics information. Once trained, our method can be plugged to existing vertex-based skinning methods with little computational overhead (<10ms), enabling real-time nonlinear dynamics. We qualitatively and quantitatively evaluate our method, and show compelling animations with soft-tissue effects, created using publicly available motion capture datasets.
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