Geometry Processing

Geometry processing focuses on developing computational methods for analyzing, manipulating, and understanding the shapes and structures of geometric objects, ranging from simple polygons to complex 3D meshes and volumes. Current research emphasizes improving the accuracy and efficiency of algorithms for tasks like shape fitting, mesh denoising, and establishing correspondences between shapes, often leveraging neural networks and deep learning architectures like convolutional neural networks to achieve this. These advancements are crucial for applications in computer graphics, computer-aided design, medical imaging, and robotics, enabling more robust and accurate processing of geometric data in various fields.