This article presents a state-of-the-art review of the applications of Artificial Intelligence (AI),
Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in …

Accommodating predicted population growth and urbanization within the UN Climate Goals
poses a significant challenge for disciplines that engage with the built environment. High …

Massive datasets and high-capacity models have driven many recent advancements in
computer vision and natural language understanding. This work presents a platform to …

We present the Habitat-Matterport 3D (HM3D) dataset. HM3D is a large-scale dataset of
1,000 building-scale 3D reconstructions from a diverse set of real-world locations. Each …

This paper proposes a novel graph-constrained generative adversarial network, whose
generator and discriminator are built upon relational architecture. The main idea is to …

This paper proposes a generative adversarial layout refinement network for automated
floorplan generation. Our architecture is an integration of a graph-constrained relational …

State-of-the-art navigation methods leverage a spatial memory to generalize to new
environments, but their occupancy maps are limited to capturing the geometric structures …

The paper presents a novel approach for vector-floorplan generation via a diffusion model,
which denoises 2D coordinates of room/door corners with two inference objectives: 1) a …

Industry 4.0 promotes the transformation of manufacturing industry to intelligence, which
demands advances in materials, devices, and systems of the construction industry …

Recent interest in design through the artificial intelligence (AI) lens is rapidly increasing.
Designers, as a special user group interacting with AI, have received more attention in the …