3DiG — 3D Interpretation and Digital Geometry

In 3DIG, we DIG

• Geometry – for structure, shape, and understanding the world in 3D
• Machine Learning – to model, learn, and reason over complex data
• Reality – Bridging digital and physical spaces with intelligence

The 3DiG laboratory was created to explore, develop, and apply innovative methodologies in the fields of digital geometry and advanced machine learning techniques for geometric data and geometric property exploitation. Research activities focus on:

• Geometry processing: Algorithms and techniques for processing, manipulating, and optimizing three-dimensional shapes and complex geometric data.

• Shape analysis involves the analysis, comparison, and classification of three-dimensional shapes, with applications in various scientific and industrial fields.

• Geometric deep learning involves developing machine learning architectures that integrate geometric constraints and knowledge into neural models.

• Medical Applications: The study of anatomical deformations for the early detection and classification of pathologies using three-dimensional data from advanced acquisition systems.

• Geometric priors in AI focus on the explicit integration of geometric knowledge to improve the robustness, efficiency, and interpretability of artificial intelligence models.