mlsanityData to 7 Oct 2026

Weakly-Supervised Photo-realistic Texture Generation for 3D Face Reconstruction

arXiv 2106.08148 ↗First posted 14 Jun 2021cs.CVcited by 3

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Abstract (arXiv)

Although much progress has been made recently in 3D face reconstruction, most previous work has been devoted to predicting accurate and fine-grained 3D shapes. In contrast, relatively little work has focused on generating high-fidelity face textures. Compared with the prosperity of photo-realistic 2D face image generation, high-fidelity 3D face texture generation has yet to be studied. In this paper, we proposed a novel UV map generation model that predicts the UV map from a single face image. The model consists of a UV sampler and a UV generator. By selectively sampling the input face image's pixels and adjusting their relative locations, the UV sampler generates an incomplete UV map that could faithfully reconstruct the original face. Missing textures in the incomplete UV map are further full-filled by the UV generator. The training is based on pseudo ground truth blended by the 3DMM texture and the input face texture, thus weakly supervised. To deal with the artifacts in the imperfect pseudo UV map, multiple partial UV map discriminators are leveraged.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 37 of its 57 references that are in the map. First posted on arXiv 14 Jun 2021.

Builds on

37 of 57 references.

References · 37

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  4. 2016Feature Pyramid Networks for Object Detectioncited by 5,021
  5. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
  6. 2014Deep Learning Face Attributes in the Wildcited by 3,679
  7. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  8. 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,833
  9. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  10. 2018Spectral Normalization for Generative Adversarial Networkscited by 1,618
  11. 2015Spatial Transformer Networkscited by 1,423
  12. 2017StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translationcited by 1,036
25 more
  1. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
  2. 2020Accelerating 3D Deep Learning with PyTorch3Dcited by 781
  3. 2019Interpreting the Latent Space of GANs for Semantic Face Editingcited by 691
  4. 2017How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)cited by 524
  5. 2019Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Setcited by 481
  6. 2014Learning Face Representation from Scratchcited by 451
  7. 2014Understanding Deep Image Representations by Inverting Themcited by 399
  8. 2016Generative Visual Manipulation on the Natural Image Manifoldcited by 348
  9. 2020Towards Fast, Accurate and Stable 3D Dense Face Alignmentcited by 219
  10. 2018Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Networkcited by 195
  11. 2018GANimation: Anatomically-aware Facial Animation from a Single Imagecited by 160
  12. 2018Nonlinear 3D Face Morphable Modelcited by 157
  13. 2019GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstructioncited by 150
  14. 2018Face Alignment in Full Pose Range: A 3D Total Solutioncited by 147
  15. 2015A Light CNN for Deep Face Representation with Noisy Labelscited by 126
  16. 2017Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesiscited by 75
  17. 2016Learning Detailed Face Reconstruction from a Single Imagecited by 71
  18. 20163D Face Reconstruction by Learning from Synthetic Datacited by 64
  19. 2017UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognitioncited by 62
  20. 20173D Face Morphable Models "In-the-Wild"cited by 44
  21. 2020Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Imagescited by 37
  22. 2020OSTeC: One-Shot Texture Completioncited by 37
  23. 2014Effective Face Frontalization in Unconstrained Imagescited by 34
  24. 2018Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalizationcited by 11
  25. 2020StyleUV: Diverse and High-fidelity UV Map Generative Modelcited by 6

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Cited by year

Citing papers per year: 2022: 2; 2023: 1.

3 papers.

  1. 2023Towards Realistic Generative 3D Face Modelscited by 20
  2. 2022A comprehensive survey on semantic facial attribute editing using generative adversarial networkscited by 3
  3. 2022Controllable Face Manipulation and UV Map Generation by Self-supervised Learningcited by 0