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Generating Animatable 3D Cartoon Faces from Single Portraits

2023-07-04 · Chuanyu Pan, Guowei Yang, TaiJiang Mu, Yu-Kun Lai

With the booming of virtual reality (VR) technology, there is a growing need for customized 3D avatars. However, traditional methods for 3D avatar modeling are either time-consuming or fail to retain similarity to the person being modeled. We present a novel framework to generate animatable 3D cartoon faces from a single portrait image. We first transfer an input real-world portrait to a stylized cartoon image with a StyleGAN. Then we propose a two-stage reconstruction method to recover the 3D cartoon face with detailed texture, which first makes a coarse estimation based on template models, and then refines the model by non-rigid deformation under landmark supervision. Finally, we propose a semantic preserving face rigging method based on manually created templates and deformation transfer. Compared with prior arts, qualitative and quantitative results show that our method achieves better accuracy, aesthetics, and similarity criteria. Furthermore, we demonstrate the capability of real-time facial animation of our 3D model.

📄 PDF Abstract BibTeX arXiv:2307.01468

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Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…
Adaptive Instance Normalization 설명 없음
Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…
R1 Regularization R_INLINE_MATH_1 Regularization is a regularization technique and gradient penalty for training [generative adversarial…
Feedforward Network A Feedforward Network, or a Multilayer Perceptron (MLP), is a neural network with solely densely connected layers. This is the classic neural network architecture of the…
StyleGAN 설명 없음

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