# Deep Deformable 3D Caricatures with Learned Shape Control arXiv: https://arxiv.org/abs/2207.14593 ยท HTML: https://mlsanity.com/paper/2207.14593/ ## Key facts - Cited by 10 papers in the map (data through 14 Oct 2026). - Builds on 36 of its 53 references that are in the map. - First posted on arXiv 29 Jul 2022. ## Builds on (most cited first, 30 of 36) - [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014) - [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019) - [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018) - [DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation](https://mlsanity.com/paper/1901.05103/) (2019) - [Implicit Neural Representations with Periodic Activation Functions](https://mlsanity.com/paper/2006.09661/) (2020) - [HyperNetworks](https://mlsanity.com/paper/1609.09106/) (2016) - [Neural Sparse Voxel Fields](https://mlsanity.com/paper/2007.11571/) (2020) - [Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations](https://mlsanity.com/paper/1906.01618/) (2019) - [PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization](https://mlsanity.com/paper/1905.05172/) (2019) - [Implicit Geometric Regularization for Learning Shapes](https://mlsanity.com/paper/2002.10099/) (2020) - [pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis](https://mlsanity.com/paper/2012.00926/) (2020) - [GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis](https://mlsanity.com/paper/2007.02442/) (2020) - [Face2Face: Real-time Face Capture and Reenactment of RGB Videos](https://mlsanity.com/paper/2007.14808/) (2020) - [AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generation](https://mlsanity.com/paper/1802.05384/) (2018) - [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://mlsanity.com/paper/1903.08527/) (2019) - [InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs](https://mlsanity.com/paper/2005.09635/) (2020) - [Generating 3D faces using Convolutional Mesh Autoencoders](https://mlsanity.com/paper/1807.10267/) (2018) - [Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network](https://mlsanity.com/paper/1803.07835/) (2018) - [Neural Volumes: Learning Dynamic Renderable Volumes from Images](https://mlsanity.com/paper/1906.07751/) (2019) - [Deep Appearance Models for Face Rendering](https://mlsanity.com/paper/1808.00362/) (2018) - [Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence](https://mlsanity.com/paper/2011.13650/) (2020) - [Learning Smooth Neural Functions via Lipschitz Regularization](https://mlsanity.com/paper/2202.08345/) (2022) - [Towards a complete 3D morphable model of the human head](https://mlsanity.com/paper/1911.08008/) (2019) - [3DN: 3D Deformation Network](https://mlsanity.com/paper/1903.03322/) (2019) - [Disentangled Representation Learning for 3D Face Shape](https://mlsanity.com/paper/1902.09887/) (2019) - [MeshGAN: Non-linear 3D Morphable Models of Faces](https://mlsanity.com/paper/1903.10384/) (2019) - [Gaussian Process Morphable Models](https://mlsanity.com/paper/1603.07254/) (2016) - [3D Face Reconstruction with Geometry Details from a Single Image](https://mlsanity.com/paper/1702.05619/) (2017) - [DeepSketch2Face: A Deep Learning Based Sketching System for 3D Face and Caricature Modeling](https://mlsanity.com/paper/1706.02042/) (2017) - [3DCaricShop: A Dataset and A Baseline Method for Single-view 3D Caricature Face Reconstruction](https://mlsanity.com/paper/2103.08204/) (2021) ## Built on by (most cited first, 10 of 10) - [3DAvatarGAN: Bridging Domains for Personalized Editable Avatars](https://mlsanity.com/paper/2301.02700/) (2023) - [Geometry Transfer for Stylizing Radiance Fields](https://mlsanity.com/paper/2402.00863/) (2024) - [HyperStyle3D: Text-Guided 3D Portrait Stylization via Hypernetworks](https://mlsanity.com/paper/2304.09463/) (2023) - [LeGO: Leveraging a Surface Deformation Network for Animatable Stylized Face Generation with One Example](https://mlsanity.com/paper/2403.15227/) (2024) - [Text-guided Image-and-Shape Editing and Generation: A Short Survey](https://mlsanity.com/paper/2304.09244/) (2023) - [StyleMM: Stylized 3D Morphable Face Model via Text-Driven Aligned Image Translation](https://mlsanity.com/paper/2508.11203/) (2025) - [AvatarTex: High-Fidelity Facial Texture Reconstruction from Single-Image Stylized Avatars](https://mlsanity.com/paper/2511.06721/) (2025) - [3Deformer: A Common Framework for Image-Guided Mesh Deformation](https://mlsanity.com/paper/2307.09892/) (2023) - [CaricatureGS: Exaggerating 3D Gaussian Splatting Faces With Gaussian Curvature](https://mlsanity.com/paper/2601.03319/) (2026) - [OMGTex: One-stage Multi-style Facial Texture Reconstruction without Geometry Guidance](https://mlsanity.com/paper/2605.25778/) (2026) ## Abstract (arXiv) A 3D caricature is an exaggerated 3D depiction of a human face. The goal of this paper is to model the variations of 3D caricatures in a compact parameter space so that we can provide a useful data-driven toolkit for handling 3D caricature deformations. To achieve the goal, we propose an MLP-based framework for building a deformable surface model, which takes a latent code and produces a 3D surface. In the framework, a SIREN MLP models a function that takes a 3D position on a fixed template surface and returns a 3D displacement vector for the input position. We create variations of 3D surfaces by learning a hypernetwork that takes a latent code and produces the parameters of the MLP. Once learned, our deformable model provides a nice editing space for 3D caricatures, supporting label-based semantic editing and point-handle-based deformation, both of which produce highly exaggerated and natural 3D caricature shapes. We also demonstrate other applications of our deformable model, such as automatic 3D caricature creation.