2025 ICCV ICCV 2025

Teeth Reconstruction and Performance Capture Using a Phone Camera

Abstract

We present the first method for personalized dental shape reconstruction and teeth-inclusive facial performance capture using only a single phone camera. Our approach democratizes high-quality facial avatars through a non-invasive, low-cost setup by addressing the ill-posed monocular capture problem with an analysis-by-synthesis approach. We introduce a representation adaptation technique that maintains both mesh and SDF representations of teeth, enabling efficient differentiable rendering while preventing teeth-lip interpenetration. To overcome alignment challenges with similar-appearing dental components, we leverage foundation models for semantic teeth segmentation and design specialized optimization objectives. Our method addresses the challenging occlusions of teeth during facial performance through optimization strategies that leverage facial structural priors, while our semantic mask rendering loss with optimal transport-based matching ensures convergence despite significant variations in initial positioning.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Science and Computer Vision and Healthcare & Medicine
🧭 Keyword Pioneer — dental reconstruction
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio