mlsanityData to 7 Oct 2026

Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example

arXiv 2105.06407 ↗First posted 12 May 2021cs.CV cs.AI cs.GRcited by 5

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Abstract (arXiv)

While makeup virtual-try-on is now widespread, parametrizing a computer graphics rendering engine for synthesizing images of a given cosmetics product remains a challenging task. In this paper, we introduce an inverse computer graphics method for automatic makeup synthesis from a reference image, by learning a model that maps an example portrait image with makeup to the space of rendering parameters. This method can be used by artists to automatically create realistic virtual cosmetics image samples, or by consumers, to virtually try-on a makeup extracted from their favorite reference image.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 10 of its 18 references that are in the map. First posted on arXiv 12 May 2021.

Builds on

10 of 18 references.

References · 10

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  2. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  3. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  4. 2013Auto-Encoding Variational Bayescited by 3,980
  5. 2017StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translationcited by 1,036
  6. 2020State of the Art on Neural Renderingcited by 276
  7. 2020Differentiable Rendering: A Surveycited by 123
  8. 2020CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfercited by 15
  9. 2019Lightweight Real-time Makeup Try-on in Mobile Browsers with Tiny CNN Models for Facial Trackingcited by 5
  10. 2021Learning Long-Term Style-Preserving Blind Video Temporal Consistencycited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 0; 2026: 1.

5 papers.

  1. 2023FICE: Text-Conditioned Fashion Image Editing With Guided GAN Inversioncited by 21
  2. 2024SCE-MAE: Selective Correspondence Enhancement with Masked Autoencoder for Self-Supervised Landmark Estimationcited by 6
  3. 2022Real-time Virtual-Try-On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Rendererscited by 2
  4. 2022Hair Color Digitization through Imaging and Deep Inverse Graphicscited by 0
  5. 2026Towards Unified Dynamic Face Landmark Detectioncited by 0