BuilDiff: 3D Building Shape Generation Using Single-Image Conditional Point Cloud Diffusion Models

Yao Wei, George Vosselman, Michael Ying Yang; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2023, pp. 2910-2919

Abstract


3D building generation with low data acquisition costs, such as single image-to-3D, becomes increasingly important. However, most of the existing single image-to-3D building creation works are restricted to those images with specific viewing angles, hence they are difficult to scale to general-view images that commonly appear in practical cases. To fill this gap, we propose a novel 3D building shape generation method exploiting point cloud diffusion models with image conditioning schemes, which demonstrates flexibility to the input images. By cooperating two conditional diffusion models and introducing a regularization strategy during denoising process, our method is able to synthesize building roofs while maintaining the overall structures. We validate our framework on two newly built datasets and extensive experiments show that our method outperforms previous works in terms of building generation quality.

Related Material


[pdf] [arXiv]
[bibtex]
@InProceedings{Wei_2023_ICCV, author = {Wei, Yao and Vosselman, George and Yang, Michael Ying}, title = {BuilDiff: 3D Building Shape Generation Using Single-Image Conditional Point Cloud Diffusion Models}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2023}, pages = {2910-2919} }