mlsanityData to 7 Oct 2026

Facial Attribute Transformers for Precise and Robust Makeup Transfer

arXiv 2104.02894 ↗First posted 7 Apr 2021cs.CV cs.AIcited by 17

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Abstract (arXiv)

In this paper, we address the problem of makeup transfer, which aims at transplanting the makeup from the reference face to the source face while preserving the identity of the source. Existing makeup transfer methods have made notable progress in generating realistic makeup faces, but do not perform well in terms of color fidelity and spatial transformation. To tackle these issues, we propose a novel Facial Attribute Transformer (FAT) and its variant Spatial FAT for high-quality makeup transfer. Drawing inspirations from the Transformer in NLP, FAT is able to model the semantic correspondences and interactions between the source face and reference face, and then precisely estimate and transfer the facial attributes. To further facilitate shape deformation and transformation of facial parts, we also integrate thin plate splines (TPS) into FAT, thus creating Spatial FAT, which is the first method that can transfer geometric attributes in addition to color and texture. Extensive qualitative and quantitative experiments demonstrate the effectiveness and superiority of our proposed FATs in the following aspects: (1) ensuring high-fidelity color transfer; (2) allowing for geometric transformation of facial parts; (3) handling facial variations (such as poses and shadows) and (4) supporting high-resolution face generation.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Builds on 28 of its 36 references that are in the map. First posted on arXiv 7 Apr 2021.

Builds on

28 of 36 references.

References · 28

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16 more
  1. 2016Robust Scene Text Recognition with Automatic Rectificationcited by 121
  2. 2017Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Lossescited by 69
  3. 2019TextScanner: Reading Characters in Order for Robust Scene Text Recognitioncited by 68
  4. 2019PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfercited by 66
  5. 2019LADN: Local Adversarial Disentangling Network for Facial Makeup and De-Makeupcited by 63
  6. 2020Collaborative Distillation for Ultra-Resolution Universal Style Transfercited by 52
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  8. 2019Ultrafast Photorealistic Style Transfer via Neural Architecture Searchcited by 39
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  16. 2019Face Beautification: Beyond Makeup Transfercited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 3; 2023: 1; 2024: 5; 2025: 4; 2026: 2.

17 papers.

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  1. 2024Stable-Makeup: When Real-World Makeup Transfer Meets Diffusion Modelcited by 44
  2. 2022EleGANt: Exquisite and Locally Editable GAN for Makeup Transfercited by 28
  3. 2022EATFormer: Improving Vision Transformer Inspired by Evolutionary Algorithmcited by 27
  4. 2021SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removalcited by 22
  5. 2021Analogous to Evolutionary Algorithm: Designing a Unified Sequence Modelcited by 20
  6. 2024Content-Style Decoupling for Unsupervised Makeup Transfer without Generating Pseudo Ground Truthcited by 15
  7. 2024Toward Tiny and High-quality Facial Makeup with Data Amplify Learningcited by 10
  8. 2024SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Modelscited by 10
  9. 2024A Multi-view Mask Contrastive Learning Graph Convolutional Neural Network for Age Estimationcited by 7
  10. 2025FLUX-Makeup: High-Fidelity, Identity-Consistent, and Robust Makeup Transfer via Diffusion Transformercited by 5
  11. 2022Semi-parametric Makeup Transfer via Semantic-aware Correspondencecited by 4
  12. 2025AvatarMakeup: Realistic Makeup Transfer for 3D Animatable Head Avatarscited by 3
5 more
  1. 2023SARA: Controllable Makeup Transfer with Spatial Alignment and Region-Adaptive Normalizationcited by 2
  2. 2025EvoMakeup: High-Fidelity and Controllable Makeup Editing with MakeupQuadcited by 2
  3. 2025Towards High-Fidelity, Identity-Preserving Real-Time Makeup Transfer: Decoupling Style Generationcited by 0
  4. 2026S3POT: Contrast-Driven Face Occlusion Segmentation via Self-Supervised Prompt Learningcited by 0
  5. 2026Facial beauty prediction fusing transfer learning and broad learning systemcited by 0