Mesh Representation

Mesh representation in computer graphics and machine learning focuses on efficiently and effectively representing 3D shapes as interconnected networks of polygons. Current research emphasizes developing novel neural network architectures, such as those based on implicit surfaces, Voronoi diagrams, and multi-resolution mesh convolutions, to generate, manipulate, and analyze meshes directly within deep learning frameworks. This allows for improved accuracy and efficiency in tasks ranging from 3D reconstruction and generation from images or text to geometry processing and physically-based rendering, impacting fields like medical imaging, robotics, and computer-aided design.