The emerging concept of digital twins outlines the pathway towards intelligent buildings. Although abundant building data carries an overwhelming amount of information, if not well exploited, the redundant and irrelevant data dimensions result in the overfitti...

Generating high-quality and diverse human images is an important yet challenging task in vision and graphics. However, existing generative models often fall short under the high diversity of clothing shapes and textures. Furthermore, the generation process is ...

Learning the spatial-temporal structure of body movements is a fundamental problem for character motion synthesis. In this work, we propose a novel neural network architecture called the Periodic Autoencoder that can learn periodic features from large unstruct...

Convolutionalneural networks (CNNs) have made great breakthroughs in two-dimensional (2D) computer vision. However, their irregular structure makes it hard to harness the potential of CNNs directly on meshes. A subdivision surface provides a hierarchical multi...

DR.JIT is a new just-in-time compiler for physically based rendering and its derivative. DR.JIT expedites research on these topics in two ways: first, it traces high-level simulation code (e.g., written in Python) and aggressively simplifies and specializes th...

Human-technology interaction is concerned with trust as an inevitable user acceptance requirement. As the applications of artificial intelligence (AI) and robotics emerge in the architecture, engineering, and construction (AEC) industry, there is an immediate ...