3D Face Reconstruction

3D face reconstruction aims to create realistic three-dimensional models of faces from images or videos, often employing techniques like 3D Morphable Models (3DMMs) and deep learning architectures such as convolutional neural networks and diffusion models. Current research emphasizes improving reconstruction accuracy, particularly for challenging scenarios involving extreme expressions, occlusions, low-resolution input, and perspective distortions, often through novel loss functions and data augmentation strategies. This field has significant implications for various applications, including forensic science, healthcare (e.g., diagnosing genetic disorders), virtual reality, and animation, by providing accurate and detailed facial representations.