3D Synthesis for Architectural Design

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. Project page: https://itingtsai.github.io/syn_arch_2025/