MeshCNN

MeshCNN is a deep learning technique designed to analyze and process 3D shapes represented as meshes—networks of interconnected vertices, edges, and faces. Unlike traditional methods that convert 3D data into simpler forms, MeshCNN operates directly on the mesh’s structure, focusing on edges as the primary units of analysis. This enables the network to better understand complex geometric features and variations. It's particularly useful for tasks like shape classification, segmentation, or recognition, providing a more accurate and efficient way to interpret detailed 3D models in various applications such as computer graphics, medical imaging, and robotics.