Shape Analysis

Shape analysis focuses on extracting meaningful information from the geometry and topology of objects, aiming to understand and quantify their form and variations. Current research emphasizes developing robust and efficient methods for 3D shape representation and analysis, employing techniques like graph convolutional networks, transformers, and autoencoders, often incorporating multi-view or cross-modal data (e.g., images and point clouds) to improve performance. These advancements have significant implications for diverse fields, including medical imaging (e.g., brain connectivity analysis), robotics (e.g., object recognition and manipulation), and urban planning (e.g., sidewalk analysis from satellite imagery), enabling more accurate and efficient processing of complex 3D data.