“WallPlan: synthesizing floorplans by learning to generate wall graphs” by Sun, Wu, Liu, Min, Zhang, et al. …

  • ©Jiahui Sun, Wenming Wu, Ligang Liu, Wenjie Min, Gaofeng Zhang, and Liping Zheng




    WallPlan: synthesizing floorplans by learning to generate wall graphs



    Floorplan generation has drawn widespread interest in the community. Recent learning-based methods for generating realistic floorplans have made significant progress while a complex heuristic post-processing is still necessary to obtain desired results. In this paper, we propose a novel wall-oriented method, called WallPlan, for automatically and efficiently generating plausible floorplans from various design constraints. We pioneer the representation of the floorplan as a wall graph with room labels and consider the floorplan generation as a graph generation. Given the boundary as input, we first initialize the boundary with windows predicted by WinNet. Then a graph generation network GraphNet and semantics prediction network LabelNet are coupled to generate the wall graph progressively by imitating graph traversal. WallPlan can be applied for practical architectural designs, especially the wall-based constraints. We conduct ablation experiments, qualitative evaluations, quantitative comparisons, and perceptual studies to evaluate our method’s feasibility, efficacy, and versatility. Intensive experiments demonstrate our method requires no post-processing, producing higher quality floorplans than state-of-the-art techniques.


    1. Scott A Arvin and Donald H House. 2002. Modeling architectural design objectives in physically based space planning. Automation in Construction 11, 2 (2002), 213–225.Google ScholarCross Ref
    2. Fan Bao, Dong-Ming Yan, Niloy J Mitra, and Peter Wonka. 2013. Generating and exploring good building layouts. ACM Transactions on Graphics (TOG) 32, 4 (2013), 1–10.Google ScholarDigital Library
    3. Ying Cao, Rynson WH Lau, and Antoni B Chan. 2014. Look over here: Attention-directing composition of manga elements. ACM Transactions on Graphics (TOG) 33, 4 (2014), 1–11.Google ScholarDigital Library
    4. Stanislas Chaillou. 2020. ArchiGAN: Artificial Intelligence x Architecture. In Architectural Intelligence. Springer, 117–127.Google Scholar
    5. Guolong Chen, Wenzhong Guo, and Yuzhong Chen. 2010. A PSO-based intelligent decision algorithm for VLSI floorplanning. Soft Computing 14, 12 (2010), 1329–1337.Google ScholarDigital Library
    6. Qi Chen, Qi Wu, Rui Tang, Yuhan Wang, Shuai Wang, and Mingkui Tan. 2020. Intelligent home 3d: Automatic 3d-house design from linguistic descriptions only. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 12625–12634.Google ScholarCross Ref
    7. Lubin Fan and Peter Wonka. 2016. A probabilistic model for exteriors of residential buildings. ACM Transactions on Graphics (TOG) 35, 5 (2016), 1–13.Google ScholarDigital Library
    8. Tian Feng, Lap-Fai Yu, Sai-Kit Yeung, Kang Kang Yin, and Kun Zhou. 2016. Crowd-driven mid-scale layout design. ACM Trans. Graph. 35, 4 (2016), 132–1.Google ScholarDigital Library
    9. Mark Hendrikx, Sebastiaan Meijer, Joeri Van Der Velden, and Alexandru Iosup. 2013. Procedural content generation for games: A survey. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 9, 1 (2013), 1–22.Google ScholarDigital Library
    10. Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter. 2017. Gans trained by a two time-scale update rule converge to a local nash equilibrium. Advances in neural information processing systems 30 (2017).Google Scholar
    11. Ruizhen Hu, Zeyu Huang, Yuhan Tang, Oliver Van Kaick, Hao Zhang, and Hui Huang. 2020. Graph2plan: Learning floorplan generation from layout graphs. ACM Transactions on Graphics (TOG) 39, 4 (2020), 118–1.Google ScholarDigital Library
    12. Graziella Laignel, Nicolas Pozin, Xavier Geffrier, Loukas Delevaux, Florian Brun, and Bastien Dolla. 2021. Floor plan generation through a mixed constraint programming-genetic optimization approach. Automation in Construction 123 (2021), 103491.Google ScholarCross Ref
    13. Manyi Li, Akshay Gadi Patil, Kai Xu, Siddhartha Chaudhuri, Owais Khan, Ariel Shamir, Changhe Tu, Baoquan Chen, Daniel Cohen-Or, and Hao Zhang. 2019. Grains: Generative recursive autoencoders for indoor scenes. ACM Transactions on Graphics (TOG) 38, 2 (2019), 1–16.Google ScholarDigital Library
    14. Han Liu, Yong-Liang Yang, Sawsan AlHalawani, and Niloy J Mitra. 2013. Constraint-aware interior layout exploration for pre-cast concrete-based buildings. The Visual Computer 29, 6 (2013), 663–673.Google ScholarDigital Library
    15. Chongyang Ma, Nicholas Vining, Sylvain Lefebvre, and Alla Sheffer. 2014. Game level layout from design specification. In Computer Graphics Forum, Vol. 33. Wiley Online Library, 95–104.Google Scholar
    16. Benachir Medjdoub and Bernard Yannou. 2000. Separating topology and geometry in space planning. Computer-aided design 32, 1 (2000), 39–61.Google Scholar
    17. Paul Merrell, Eric Schkufza, and Vladlen Koltun. 2010. Computer-generated residential building layouts. In ACM SIGGRAPH Asia 2010 papers. 1–12.Google Scholar
    18. Jeremy Michalek, Ruchi Choudhary, and Panos Papalambros. 2002. Architectural layout design optimization. Engineering optimization 34, 5 (2002), 461–484.Google Scholar
    19. Jeremy Michalek and Panos Papalambros. 2002. Interactive design optimization of architectural layouts. Engineering optimization 34, 5 (2002), 485–501.Google Scholar
    20. Nelson Nauata, Kai-Hung Chang, Chin-Yi Cheng, Greg Mori, and Yasutaka Furukawa. 2020. House-gan: Relational generative adversarial networks for graph-constrained house layout generation. In European Conference on Computer Vision. Springer, 162–177.Google ScholarDigital Library
    21. Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang, Hang Chu, Chin-Yi Cheng, and Yasutaka Furukawa. 2021. House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 13632–13641.Google ScholarCross Ref
    22. Peter O’Donovan, Aseem Agarwala, and Aaron Hertzmann. 2014. Learning layouts for single-pagegraphic designs. IEEE transactions on visualization and computer graphics 20, 8 (2014), 1200–1213.Google ScholarDigital Library
    23. Xufang Pang, Ying Cao, Rynson WH Lau, and Antoni B Chan. 2016. Directing user attention via visual flow on web designs. ACM Transactions on Graphics (TOG) 35, 6 (2016), 1–11.Google ScholarDigital Library
    24. Wamiq Para, Paul Guerrero, Tom Kelly, Leonidas J Guibas, and Peter Wonka. 2021. Generative layout modeling using constraint graphs. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 6690–6700.Google ScholarCross Ref
    25. Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros. 2016. Context encoders: Feature learning by inpainting. In Proceedings of the IEEE conference on computer vision and pattern recognition. 2536–2544.Google ScholarCross Ref
    26. Chi-Han Peng, Yong-Liang Yang, Fan Bao, Daniel Fink, Dong-Ming Yan, Peter Wonka, and Niloy J Mitra. 2016. Computational network design from functional specifications. ACM Transactions on Graphics (TOG) 35, 4 (2016), 1–12.Google ScholarDigital Library
    27. Chi-Han Peng, Yong-Liang Yang, and Peter Wonka. 2014. Computing layouts with deformable templates. ACM Transactions on Graphics (TOG) 33, 4 (2014), 1–11.Google ScholarDigital Library
    28. Daniel Ritchie, Kai Wang, and Yu-an Lin. 2019. Fast and flexible indoor scene synthesis via deep convolutional generative models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 6182–6190.Google ScholarCross Ref
    29. Julian F Rosser, Gavin Smith, and Jeremy G Morley. 2017. Data-driven estimation of building interior plans. International Journal of Geographical Information Science 31, 8 (2017), 1652–1674.Google ScholarDigital Library
    30. Carl Sechen. 2012. VLSI placement and global routing using simulated annealing. Vol. 54. Springer Science & Business Media.Google Scholar
    31. Krishnendra Shekhawat, Nitant Upasani, Sumit Bisht, and Rahil N Jain. 2021. A tool for computer-generated dimensioned floorplans based on given adjacencies. Automation in Construction 127 (2021), 103718.Google ScholarCross Ref
    32. T Singha, HS Dutta, and M De. 2012. Optimization of floor-planning using genetic algorithm. Procedia Technology 4 (2012), 825–829.Google ScholarCross Ref
    33. Carlos A Vanegas, Tom Kelly, Basil Weber, Jan Halatsch, Daniel G Aliaga, and Pascal Müller. 2012. Procedural generation of parcels in urban modeling. In Computer graphics forum, Vol. 31. Wiley Online Library, 681–690.Google Scholar
    34. Kai Wang, Yu-An Lin, Ben Weissmann, Manolis Savva, Angel X Chang, and Daniel Ritchie. 2019. Planit: Planning and instantiating indoor scenes with relation graph and spatial prior networks. ACM Transactions on Graphics (TOG) 38, 4 (2019), 1–15.Google ScholarDigital Library
    35. KaiWang, Manolis Savva, Angel X Chang, and Daniel Ritchie. 2018. Deep convolutional priors for indoor scene synthesis. ACM Transactions on Graphics (TOG) 37, 4 (2018), 1–14.Google Scholar
    36. Kai Wang, Xianghao Xu, Leon Lei, Selena Ling, Natalie Lindsay, Angel X Chang, Manolis Savva, and Daniel Ritchie. 2021. Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms. In Computer Graphics Forum, Vol. 40. Wiley Online Library, 57–69.Google Scholar
    37. Xiao-Yu Wang and Kang Zhang. 2020. Generating layout designs from high-level specifications. Automation in Construction 119 (2020), 103288.Google ScholarCross Ref
    38. Wenming Wu, Lubin Fan, Ligang Liu, and Peter Wonka. 2018. MIQP-based Layout Design for Building Interiors. In Computer Graphics Forum, Vol. 37. Wiley Online Library, 511–521.Google Scholar
    39. Wenming Wu, Xiao-Ming Fu, Rui Tang, Yuhan Wang, Yu-Hao Qi, and Ligang Liu. 2019. Data-driven interior plan generation for residential buildings. ACM Transactions on Graphics (TOG) 38, 6 (2019), 1–12.Google ScholarDigital Library
    40. Xuyong Yang, Tao Mei, Ying-Qing Xu, Yong Rui, and Shipeng Li. 2016. Automatic generation of visual-textual presentation layout. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 12, 2 (2016), 1–22.Google ScholarDigital Library
    41. Yong-Liang Yang, Jun Wang, Etienne Vouga, and Peter Wonka. 2013. Urban pattern: Layout design by hierarchical domain splitting. ACM Transactions on Graphics (TOG) 32, 6 (2013), 1–12.Google ScholarDigital Library
    42. Yi-Ting Yeh, Katherine Breeden, Lingfeng Yang, Matthew Fisher, and Pat Hanrahan. 2013. Synthesis of tiled patterns using factor graphs. ACM Transactions on Graphics (TOG) 32, 1 (2013), 1–13.Google ScholarDigital Library
    43. Yi-Ting Yeh, Lingfeng Yang, Matthew Watson, Noah D Goodman, and Pat Hanrahan. 2012. Synthesizing open worlds with constraints using locally annealed reversible jump mcmc. ACM Transactions on Graphics (TOG) 31, 4 (2012), 1–11.Google ScholarDigital Library
    44. Zaiwei Zhang, Zhenpei Yang, Chongyang Ma, Linjie Luo, Alexander Huth, Etienne Vouga, and Qixing Huang. 2020. Deep generative modeling for scene synthesis via hybrid representations. ACM Transactions on Graphics (TOG) 39, 2 (2020), 1–21.Google ScholarDigital Library
    45. Xinru Zheng, Xiaotian Qiao, Ying Cao, and Rynson WH Lau. 2019. Content-aware generative modeling of graphic design layouts. ACM Transactions on Graphics (TOG) 38, 4 (2019), 1–15.Google ScholarDigital Library
    46. Lichen Zhou, Chuang Zhang, and Ming Wu. 2018. D-linknet: Linknet with pretrained encoder and dilated convolution for high resolution satellite imagery road extraction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 182–186.Google ScholarCross Ref
    47. Yang Zhou, Zachary While, and Evangelos Kalogerakis. 2019. Scenegraphnet: Neural message passing for 3d indoor scene augmentation. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 7384–7392.Google ScholarCross Ref

ACM Digital Library Publication:

Overview Page: