ArchiDiff: Interactive design of 3D architectural forms generated from a single image
3D Reconstruction Using Images has made strides in small-scale, uncomplicated scenes but struggles with complex, large-scale architectural forms. Targeting early-stage architectural design, we introduce ArchiDiff, a platform for 3D architectural form generation and editing from images to point cloud...
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| Vydáno v: | Computers in industry Ročník 168; s. 104275 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
01.06.2025
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| ISSN: | 0166-3615 |
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| Abstract | 3D Reconstruction Using Images has made strides in small-scale, uncomplicated scenes but struggles with complex, large-scale architectural forms. Targeting early-stage architectural design, we introduce ArchiDiff, a platform for 3D architectural form generation and editing from images to point clouds. First, we curated a dataset specifically tailored for architectural design, ArchiCloudNet. Second, we proposed a 3D generation method using a conditional denoising diffusion model, with an arbitrary object segmentation model to enhance recognition capabilities in complex input. Finally, we incorporate an interactive feature enabling instantaneous 2D image editing through simple drag-and-drops with simultaneous updates to 3D forms, giving designers improved control. We evaluated ArchiDiff’s generation accuracy against cutting-edge baselines on ArchiCloudNet and two other datasets, RealCity3D and BuildingNet. We also validated it with real sketches from early-stage architectural design. The experiments indicated that our model could generate accurate architectural point clouds, providing rapid-response modification and effective processing of complex backgrounds. Demostration: http://39.101.72.109:3000/archidiff.
•A tailored dataset for architecture containing 3D forms and 2D images.•Accurate generation of complex architectural forms through diffusion model.•Facilitating direct 2D-to-3D updates, enhancing design interactivity and flexibility.•Leading performance in architectural design scenarios among baseline models. |
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| AbstractList | 3D Reconstruction Using Images has made strides in small-scale, uncomplicated scenes but struggles with complex, large-scale architectural forms. Targeting early-stage architectural design, we introduce ArchiDiff, a platform for 3D architectural form generation and editing from images to point clouds. First, we curated a dataset specifically tailored for architectural design, ArchiCloudNet. Second, we proposed a 3D generation method using a conditional denoising diffusion model, with an arbitrary object segmentation model to enhance recognition capabilities in complex input. Finally, we incorporate an interactive feature enabling instantaneous 2D image editing through simple drag-and-drops with simultaneous updates to 3D forms, giving designers improved control. We evaluated ArchiDiff’s generation accuracy against cutting-edge baselines on ArchiCloudNet and two other datasets, RealCity3D and BuildingNet. We also validated it with real sketches from early-stage architectural design. The experiments indicated that our model could generate accurate architectural point clouds, providing rapid-response modification and effective processing of complex backgrounds. Demostration: http://39.101.72.109:3000/archidiff.
•A tailored dataset for architecture containing 3D forms and 2D images.•Accurate generation of complex architectural forms through diffusion model.•Facilitating direct 2D-to-3D updates, enhancing design interactivity and flexibility.•Leading performance in architectural design scenarios among baseline models. |
| ArticleNumber | 104275 |
| Author | Lin, Borong Lu, Shuai Gao, Wen Xu, Pengjian Li, Jizhizi Yin, Jun Wu, Chenglin |
| Author_xml | – sequence: 1 givenname: Jun surname: Yin fullname: Yin, Jun organization: Shenzhen International Graduate School, Tsinghua University, Shenzhen, China – sequence: 2 givenname: Wen surname: Gao fullname: Gao, Wen organization: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, China – sequence: 3 givenname: Jizhizi surname: Li fullname: Li, Jizhizi organization: The University of Sydney, NSW, Australia – sequence: 4 givenname: Pengjian surname: Xu fullname: Xu, Pengjian organization: Zoomtech Engineering co., Ltd, Guangzhou, China – sequence: 5 givenname: Chenglin surname: Wu fullname: Wu, Chenglin organization: Shenzhen International Graduate School, Tsinghua University, Shenzhen, China – sequence: 6 givenname: Borong surname: Lin fullname: Lin, Borong organization: School of Architecture, Tsinghua University, Beijing, China – sequence: 7 givenname: Shuai orcidid: 0000-0003-3772-1613 surname: Lu fullname: Lu, Shuai email: shuai.lu@sz.tsinghua.edu.cn organization: Shenzhen International Graduate School, Tsinghua University, Shenzhen, China |
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