Shape Retrieval

Shape retrieval focuses on efficiently searching and retrieving 3D models based on various queries, including text descriptions or images. Current research emphasizes improving retrieval accuracy by leveraging multimodal data (text, images, 3D models) and contrastive learning methods, often employing deep learning architectures to generate robust embeddings. A key challenge lies in handling occlusions and unseen objects in single-view retrieval, while advancements are also being made in handling heterogeneous data types like hand gestures and biological macromolecules in cryo-electron tomograms. These improvements have significant implications for applications ranging from virtual and augmented reality to biological image analysis.