ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2505.04387
52
0

Geometry-Aware Texture Generation for 3D Head Modeling with Artist-driven Control

7 May 2025
Amin Fadaeinejad
Abdallah Dib
L. G. Hafemann
Emeline Got
Trevor Anderson
Amaury Depierre
N. Troje
M. Brubaker
M. Carbonneau
    3DH
ArXivPDFHTML
Abstract

Creating realistic 3D head assets for virtual characters that match a precise artistic vision remains labor-intensive. We present a novel framework that streamlines this process by providing artists with intuitive control over generated 3D heads. Our approach uses a geometry-aware texture synthesis pipeline that learns correlations between head geometry and skin texture maps across different demographics. The framework offers three levels of artistic control: manipulation of overall head geometry, adjustment of skin tone while preserving facial characteristics, and fine-grained editing of details such as wrinkles or facial hair. Our pipeline allows artists to make edits to a single texture map using familiar tools, with our system automatically propagating these changes coherently across the remaining texture maps needed for realistic rendering. Experiments demonstrate that our method produces diverse results with clean geometries. We showcase practical applications focusing on intuitive control for artists, including skin tone adjustments and simplified editing workflows for adding age-related details or removing unwanted features from scanned models. This integrated approach aims to streamline the artistic workflow in virtual character creation.

View on arXiv
@article{fadaeinejad2025_2505.04387,
  title={ Geometry-Aware Texture Generation for 3D Head Modeling with Artist-driven Control },
  author={ Amin Fadaeinejad and Abdallah Dib and Luiz Gustavo Hafemann and Emeline Got and Trevor Anderson and Amaury Depierre and Nikolaus F. Troje and Marcus A. Brubaker and Marc-André Carbonneau },
  journal={arXiv preprint arXiv:2505.04387},
  year={ 2025 }
}
Comments on this paper