Awesome Makeup Transfer
A curated list of resources for makeup and hairstyle transfer research using computer vision and generative AI.
What is Awesome Makeup Transfer?
Awesome Makeup Transfer is a curated GitHub repository listing academic papers, datasets, and resources related to makeup transfer and hairstyle transfer in computer vision. It compiles research on using generative models like GANs and diffusion models to realistically apply or remove makeup and hairstyles from facial images. The project organizes the latest advancements from top conferences and provides links to code and datasets.
Computer vision researchers, AI engineers, and students working on facial image synthesis, generative models, or virtual try-on applications. It's particularly useful for those exploring makeup/hairstyle transfer, face beautification, or adversarial attacks on face recognition.
It saves significant time in literature review by aggregating scattered resources into a single, well-structured list. The inclusion of datasets and code links lowers the barrier to entry for experimenting with state-of-the-art methods, fostering reproducibility and collaboration in the research community.
Overview
A curated list of Awesome Makeup Transfer resources
Use Cases
Best For
- Finding the latest research papers on GAN-based makeup transfer
Related Projects
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