AvatarMakeup: Realistic Makeup Transfer for 3D Animatable Head Avatars
Yiming Zhong, Xiaolin Zhang, Ligang Liu, Yao Zhao, and Yunchao Wei

TL;DR
AvatarMakeup introduces a novel 3D makeup transfer method for avatars that ensures realistic, consistent, and detailed makeup effects across expressions and viewpoints by leveraging diffusion models and a coherence optimization technique.
Contribution
The paper presents a specialized 3D makeup transfer approach using diffusion models and a Coherent Duplication method to improve realism, consistency, and control in avatar customization.
Findings
Achieves state-of-the-art makeup transfer quality.
Ensures consistent appearance across dynamic expressions.
Provides precise control over fine makeup details.
Abstract
Similar to facial beautification in real life, 3D virtual avatars require personalized customization to enhance their visual appeal, yet this area remains insufficiently explored. Although current 3D Gaussian editing methods can be adapted for facial makeup purposes, these methods fail to meet the fundamental requirements for achieving realistic makeup effects: 1) ensuring a consistent appearance during drivable expressions, 2) preserving the identity throughout the makeup process, and 3) enabling precise control over fine details. To address these, we propose a specialized 3D makeup method named AvatarMakeup, leveraging a pretrained diffusion model to transfer makeup patterns from a single reference photo of any individual. We adopt a coarse-to-fine idea to first maintain the consistent appearance and identity, and then to refine the details. In particular, the diffusion model is…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVirtual Reality Applications and Impacts · Human Motion and Animation · Augmented Reality Applications
