Deep Deformable 3D Caricatures with Learned Shape Control

Author:

Jung Yucheol1,Jang Wonjong1,Kim Soongjin1,Yang Jiaolong2,Tong Xin2,Lee Seungyong1

Affiliation:

1. POSTECH, South Korea

2. Microsoft Research Asia, China

Funder

Korea Creative Content Agency

Institute for Information and communications Technology Promotion

Publisher

ACM

Reference41 articles.

1. A morphable model for the synthesis of 3D faces

2. Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model

3. Facewarehouse: A 3d facial expression database for visual computing;Cao Chen;IEEE Trans. Vis. Comput. Graph.,2013

4. pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis

5. Shiyang Cheng , Michael Bronstein , Yuxiang Zhou , Irene Kotsia , Maja Pantic , and Stefanos Zafeiriou . 2019 . Meshgan: Non-linear 3d morphable models of faces. arXiv preprint arXiv:1903.10384(2019). Shiyang Cheng, Michael Bronstein, Yuxiang Zhou, Irene Kotsia, Maja Pantic, and Stefanos Zafeiriou. 2019. Meshgan: Non-linear 3d morphable models of faces. arXiv preprint arXiv:1903.10384(2019).

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2. 3DAvatarGAN: Bridging Domains for Personalized Editable Avatars;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

3. Face Editing Using Part‐Based Optimization of the Latent Space;Computer Graphics Forum;2023-05

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