2025 WACV WACV 2025

3D Synthesis for Architectural Design

Abstract

We introduce a 3D synthesis method for architectural design to allow for the efficient generation of diverse and realistic building designs. In spite of advances in 3D synthesis current off-the-shelf 3D synthesis techniques are inappropriate for architectural design: they are trained primarily on isolated objects have limited diversity blend building facades with background and produce overly complex geometry that is difficult to edit or manipulate a major issue in an iterative design process. We propose an alternative pipeline that integrates auto-generated coarse models with segment-wise texture inpainting and semantics-based editing resulting in diverse style-consistent and shape-precise designs. We show through qualitative and quantitative experiments that our pipeline generates more diverse visually appealing architectures with clean geometries without the need for any extensive training.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Science
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Knowledge & Reasoning, Machine Learning, Natural Language Processing, Reinforcement Learning, Speech & Audio