mlsanityData to 7 Oct 2026

BareSkinNet: De-makeup and De-lighting via 3D Face Reconstruction

arXiv 2209.09029 ↗First posted 19 Sep 2022cs.CV cs.GRcited by 10

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Abstract (arXiv)

We propose BareSkinNet, a novel method that simultaneously removes makeup and lighting influences from the face image. Our method leverages a 3D morphable model and does not require a reference clean face image or a specified light condition. By combining the process of 3D face reconstruction, we can easily obtain 3D geometry and coarse 3D textures. Using this information, we can infer normalized 3D face texture maps (diffuse, normal, roughness, and specular) by an image-translation network. Consequently, reconstructed 3D face textures without undesirable information will significantly benefit subsequent processes, such as re-lighting or re-makeup. In experiments, we show that BareSkinNet outperforms state-of-the-art makeup removal methods. In addition, our method is remarkably helpful in removing makeup to generate consistent high-fidelity texture maps, which makes it extendable to many realistic face generation applications. It can also automatically build graphic assets of face makeup images before and after with corresponding 3D data. This will assist artists in accelerating their work, such as 3D makeup avatar creation.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 51 of its 79 references that are in the map. First posted on arXiv 19 Sep 2022.

Builds on

51 of 79 references.

References · 51

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
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  12. 20193D Morphable Face Models -- Past, Present and Futurecited by 269
38 more
  1. 2020StyleRig: Rigging StyleGAN for 3D Control over Portrait Imagescited by 267
  2. 2022EMOCA: Emotion Driven Monocular Face Capture and Animationcited by 254
  3. 2020FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Predictioncited by 196
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  5. 2017MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstructioncited by 163
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  7. 2019Single Image Portrait Relightingcited by 152
  8. 2019GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstructioncited by 150
  9. 2017SfSNet: Learning Shape, Reflectance and Illuminance of Faces in the Wildcited by 110
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  12. 2022FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Datasetcited by 98
  13. 2020Learning Formation of Physically-Based Face Attributescited by 94
  14. 2017Self-supervised Multi-level Face Model Learning for Monocular Reconstruction at over 250 Hzcited by 91
  15. 2020AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"cited by 91
  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. 2017Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regressioncited by 66
  19. 2019PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfercited by 66
  20. 2019LADN: Local Adversarial Disentangling Network for Facial Makeup and De-Makeupcited by 63
  21. 2017UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognitioncited by 62
  22. 2017Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translationcited by 56
  23. 2020A Morphable Face Albedo Modelcited by 54
  24. 2021Anycost GANs for Interactive Image Synthesis and Editingcited by 54
  25. 2020GIF: Generative Interpretable Facescited by 53
  26. 2017Towards Large-Pose Face Frontalization in the Wildcited by 50
  27. 2021AvatarMe++: Facial Shape and BRDF Inference with Photorealistic Rendering-Aware GANscited by 49
  28. 2020High-Fidelity 3D Digital Human Head Creation from RGB-D Selfiescited by 47
  29. 2020Portrait Shadow Manipulationcited by 42
  30. 2021Towards High Fidelity Face Relighting with Realistic Shadowscited by 42
  31. 2020PIE: Portrait Image Embedding for Semantic Controlcited by 41
  32. 2020OSTeC: One-Shot Texture Completioncited by 37
  33. 2021Normalized Avatar Synthesis Using StyleGAN and Perceptual Refinementcited by 36
  34. 2021Lipstick ain't enough: Beyond Color Matching for In-the-Wild Makeup Transfercited by 35
  35. 2017Synthesizing Normalized Faces from Facial Identity Featurescited by 33
  36. 2016Photorealistic Facial Texture Inference Using Deep Neural Networkscited by 32
  37. 2022EleGANt: Exquisite and Locally Editable GAN for Makeup Transfercited by 28
  38. 2020Light Stage Super-Resolution: Continuous High-Frequency Relightingcited by 20

50 most cited of 51 All 51 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 4; 2025: 2; 2026: 1.

10 papers.

  1. 2023EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modelingcited by 101
  2. 2023Controllable Light Diffusion for Portraitscited by 11
  3. 2023Makeup Extraction of 3D Representation via Illumination-Aware Image Decompositioncited by 8
  4. 2024Makeup Prior Models for 3D Facial Makeup Estimation and Applicationscited by 7
  5. 2025FreeUV: Ground-Truth-Free Realistic Facial UV Texture Recovery via Cross-Assembly Inference Strategycited by 7
  6. 2024COMPOSE: Comprehensive Portrait Shadow Editingcited by 6
  7. 2024BeautyBank: Encoding Facial Makeup in Latent Spacecited by 4
  8. 2025FFHQ-Makeup: Paired Synthetic Makeup Dataset with Facial Consistency Across Multiple Stylescited by 2
  9. 20243D Face Modeling via Weakly-supervised Disentanglement Network joint Identity-consistency Priorcited by 1
  10. 2026Supervised makeup transfer with a curated dataset: Decoupling identity and makeup features for enhanced transformationcited by 1