MakeupMirror: Improving Facial Attribute Preservation in Diffusion Models for Makeup Transfer

1. 1Build a diffusion-based makeup transfer model using Stable-Makeup as a baseline
2. 2Configure the model to prioritize facial attribute preservation
3. 3Test the model on a dataset of diverse faces and makeup styles
4. 4Apply the MakeupMirror approach to improve identity and skin color preservation
5. 5Evaluate the results using metrics such as facial similarity and makeup transfer accuracy

Computer vision engineers and researchers on a team can benefit from this work to improve the accuracy of virtual try-on models, while product managers can leverage this technology to enhance online shopping experiences

💡 Preserving facial attributes such as identity and skin color is crucial for realistic virtual try-on experiences

🔍 Improve virtual try-on with MakeupMirror, a new approach for preserving facial attributes in diffusion-based makeup transfer models