The paper details a 3D to 2D encoding method, which can store complex digital 3D models of architecture within a single image. The proposed encoding works in combination with a point cloud notation and a sequential slicing operation where each slice of points is stored as a single row of pixels in the UV space of a 1024 × 1024 image. The performance of the notation system is compared between a StyleGan2 and existing image editing methods and evaluated through the production of new 3D models of houses with material attributes. The uncovered findings maintain the relatively high level of detail stored through the encoding while allowing for innovative ways of form-finding—producing new and unseen 3d models of architectural houses.


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    Titel :

    Collapsing Complexities: Encoding Multidimensional Architecture Models into Images


    Weitere Titelangaben:

    Computational Design and Robotic Fabrication


    Beteiligte:
    Yuan, Philip F. (Herausgeber:in) / Chai, Hua (Herausgeber:in) / Yan, Chao (Herausgeber:in) / Li, Keke (Herausgeber:in) / Sun, Tongyue (Herausgeber:in) / Sándor, Viktória (Autor:in) / Bank, Mathias (Autor:in) / Schinegger, Kristina (Autor:in) / Rutzinger, Stefan (Autor:in)

    Kongress:

    The International Conference on Computational Design and Robotic Fabrication ; 2022 June 27, 2022 - July 05, 2022



    Erscheinungsdatum :

    2023-04-04


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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