Geometric deep learning (GDL) is based on neural network architectures that incorporate
and process symmetry information. GDL bears promise for molecular modelling applications …

Point cloud learning has lately attracted increasing attention due to its wide applications in
many areas, such as computer vision, autonomous driving, and robotics. As a dominating …

The architecture, engineering and construction (AEC) industry is experiencing a
technological revolution driven by booming digitisation and automation. Advances in …

Recently, the advancement of deep learning (DL) in discriminative feature learning from 3-D
LiDAR data has led to rapid development in the field of autonomous driving. However …

Generative AI has made significant progress in recent years, with text-guided content
generation being the most practical as it facilitates interaction between human instructions …

Deep learning is catalyzing a scientific revolution fueled by big data, accessible toolkits, and
powerful computational resources, impacting many fields, including protein structural …

Analyzing the geometric and semantic properties of 3D point clouds through the deep
networks is still challenging due to the irregularity and sparsity of samplings of their …

Point cloud is a widely used 3D data form, which can be produced by depth sensors, such
as Light Detection and Ranging (LIDAR) and RGB-D cameras. Being unordered and …

People touch their face 23 times an hour, they cross their arms and legs, put their hands on
their hips, etc. While many images of people contain some form of self-contact, current 3D …

We propose a data-driven scene flow estimation algorithm exploiting the observation that
many 3D scenes can be explained by a collection of agents moving as rigid bodies. At the …