mlsanityData to 7 Oct 2026

Controllable 3D Generative Adversarial Face Model via Disentangling Shape and Appearance

arXiv 2208.14263 ↗First posted 30 Aug 2022cs.CVcited by 8

Not on the map. Why?

Abstract (arXiv)

3D face modeling has been an active area of research in computer vision and computer graphics, fueling applications ranging from facial expression transfer in virtual avatars to synthetic data generation. Existing 3D deep learning generative models (e.g., VAE, GANs) allow generating compact face representations (both shape and texture) that can model non-linearities in the shape and appearance space (e.g., scatter effects, specularities, etc.). However, they lack the capability to control the generation of subtle expressions. This paper proposes a new 3D face generative model that can decouple identity and expression and provides granular control over expressions. In particular, we propose using a pair of supervised auto-encoder and generative adversarial networks to produce high-quality 3D faces, both in terms of appearance and shape. Experimental results in the generation of 3D faces learned with holistic expression labels, or Action Unit labels, show how we can decouple identity and expression; gaining fine-control over expressions while preserving identity.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 27 of its 60 references that are in the map. First posted on arXiv 30 Aug 2022.

Builds on

27 of 60 references.

References · 27

  1. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  2. 2017Improved Training of Wasserstein GANscited by 2,223
  3. 2014Conditional Generative Adversarial Netscited by 2,152
  4. 2020Face2Face: Real-time Face Capture and Reenactment of RGB Videoscited by 631
  5. 2016Conditional Image Synthesis With Auxiliary Classifier GANscited by 562
  6. 20193D Morphable Face Models -- Past, Present and Futurecited by 269
  7. 2018Generating 3D faces using Convolutional Mesh Autoencoderscited by 267
  8. 2018Deep Video Portraitscited by 265
  9. 2020FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Predictioncited by 196
  10. 2018Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Networkcited by 195
  11. 2018Deep Appearance Models for Face Renderingcited by 164
  12. 2019GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstructioncited by 150
15 more
  1. 2020Learning Formation of Physically-Based Face Attributescited by 94
  2. 2020AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"cited by 91
  3. 2017Variational Autoencoders for Deforming 3D Mesh Modelscited by 69
  4. 20163D Face Reconstruction by Learning from Synthetic Datacited by 64
  5. 2017UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognitioncited by 62
  6. 2017Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translationcited by 56
  7. 2019Disentangled Representation Learning for 3D Face Shapecited by 48
  8. 2019Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networkscited by 34
  9. 2018Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Modelcited by 28
  10. 20193DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translationcited by 27
  11. 2021MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulationcited by 24
  12. 2018High Quality Facial Surface and Texture Synthesis via Generative Adversarial Networkscited by 22
  13. 2019Synthesizing facial photometries and corresponding geometries using generative adversarial networkscited by 11
  14. 2021FaceTuneGAN: Face Autoencoder for Convolutional Expression Transfer Using Neural Generative Adversarial Networkscited by 9
  15. 2019A Decoupled 3D Facial Shape Model by Adversarial Trainingcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 2; 2025: 1; 2026: 1.

8 papers.

  1. 2023Towards Realistic Generative 3D Face Modelscited by 20
  2. 2024FoundHand: Large-Scale Domain-Specific Learning for Controllable Hand Image Generationcited by 8
  3. 2025UVGS: Reimagining Unstructured 3D Gaussian Splatting using UV Mappingcited by 8
  4. 2023FitDiff: Robust monocular 3D facial shape and reflectance estimation using Diffusion Modelscited by 5
  5. 2024Synthesizing Iris Images using Generative Adversarial Networks: Survey and Comparative Analysiscited by 5
  6. 20233D-Aware Talking-Head Video Motion Transfercited by 4
  7. 2026Spherical Geometry Diffusion: Generating High-quality 3D Face Geometry via Sphere-anchored Representationscited by 1
  8. 2023MUNCH: Modelling Unique 'N Controllable Headscited by 0