Multimodal Conditional 3D Face Geometry Generation

• URL: http://arxiv.org/abs/2407.01074v2
• Date: Tue, 02 Sep 2025 07:17:39 GMT
• Title: Multimodal Conditional 3D Face Geometry Generation
• Abstract summary: We demonstrate 3D faces generated from artistic sketches, portrait photos, Canny edges, FLAME face model parameters, 2D face landmarks, or text prompts.<n>Our approach is based on a diffusion process that generates 3D geometry in a 2D parameterized UV domain.
• Score: 17.262213841207338
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a new method for multimodal conditional 3D face geometry generation that allows user-friendly control over the output identity and expression via a number of different conditioning signals. Within a single model, we demonstrate 3D faces generated from artistic sketches, portrait photos, Canny edges, FLAME face model parameters, 2D face landmarks, or text prompts. Our approach is based on a diffusion process that generates 3D geometry in a 2D parameterized UV domain. Geometry generation passes each conditioning signal through a set of cross-attention layers (IP-Adapter), one set for each user-defined conditioning signal. The result is an easy-to-use 3D face generation tool that produces topology-consistent, high-quality geometry with fine-grain user control.

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