Volumetric Effect

Volumetric effect research focuses on representing and manipulating three-dimensional objects and scenes as volumes, aiming for accurate and efficient computation of properties like volume, shape, and appearance. Current research employs diverse approaches, including neural networks (e.g., for real-time rendering and 3D reconstruction from incomplete data), stochastic geometry models (for representing opaque solids), and transformer architectures (for medical image segmentation). These advancements have significant implications for various fields, improving medical image analysis (e.g., liver volumetry, tumor classification), computer graphics (e.g., realistic rendering of complex materials), and robotics (e.g., efficient exploration planning).