Skinning a Parameterization of Three-Dimensional Space for Neural Network Cloth

no code implementations • 8 Jun 2020 • Jane Wu, Zhenglin Geng, Hui Zhou, Ronald Fedkiw

We present a novel learning framework for cloth deformation by embedding virtual cloth into a tetrahedral mesh that parametrizes the volumetric region of air surrounding the underlying body.

Recovering Geometric Information with Learned Texture Perturbations

no code implementations • 20 Jan 2020 • Jane Wu, Yongxu Jin, Zhenglin Geng, Hui Zhou, Ronald Fedkiw

Regularization is used to avoid overfitting when training a neural network; unfortunately, this reduces the attainable level of detail hindering the ability to capture high-frequency information present in the training data.

Deep Energies for Estimating Three-Dimensional Facial Pose and Expression

no code implementations • 7 Dec 2018 • Michael Bao, Jane Wu, Xinwei Yao, Ronald Fedkiw

While much progress has been made in capturing high-quality facial performances using motion capture markers and shape-from-shading, high-end systems typically also rely on rotoscope curves hand-drawn on the image.