Deep learning methods have achieved great success in analyzing traditional data such as
texts, sounds, images and videos. More and more research works are carrying out to extend …

Higher dimensional data such as video and 3D are the leading edge of multimedia retrieval
and computer vision research. In this survey, we give a comprehensive overview and key …

This paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM)
designed for embodied interaction, exploring a universal 3D object understanding with 3D …

Polygonal meshes provide an efficient representation for 3D shapes. They explicitly
captureboth shape surface and topology, and leverage non-uniformity to represent large flat …

Multi-view projection methods have demonstrated their ability to reach state-of-the-art
performance on 3D shape recognition. Those methods learn different ways to aggregate …

We explore the effect of geometric structure descriptors on extracting reliable
correspondences and obtaining accurate registration for point cloud registration. The point …

Abstract 3D shape recognition has attracted much attention recently. Its recent advances
advocate the usage of deep features and achieve the state-of-the-art performance. However …

Geometric deep learning is an umbrella term for emerging techniques attempting to
generalize (structured) deep neural models to non-Euclidean domains, such as graphs and …

Abstract 3D shape models are becoming widely available and easier to capture, making
available 3D information crucial for progress in object classification. Current state-of-the-art …

A longstanding question in computer vision concerns the representation of 3D shapes for
recognition: should 3D shapes be represented with descriptors operating on their native 3D …