2025/05/07 by Amin Fadaeinejad, Abdallah Dib, Fadaeinejad, Amin +15
Computer Science · Engineering · #3D Shape Modeling and Analysis #Face recognition and analysis #Generative Adversarial Networks and Image Synthesis #Head (geology) #Image editing #Pipeline (software) #Process (computing) #Texture (cosmology) #Texture synthesis #Tone (literature) #Workflow
paper · pdf · doi:10.48550/arxiv.2505.04387
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2025/05/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.