---
res:
  bibo_abstract:
  - "Deploying digital twins across the broader building stock is constrained by a
    key bottleneck: high-quality 3D content from LiDAR or photogrammetry remains labor-intensive
    and difficult to scale. We introduce Generative Twins (GT), a workflow that shifts
    digital twin creation from explicit geometric reconstruction toward probabilistic
    3D synthesis. The pipeline takes a\r\nsingle street-level façade photograph, corrects
    perspective distortion and removes occlusions, uses an instruction-conditioned
    multimodal image model to synthesise an isometric view of the building, and passes
    that view to an image-to-3D reconstruction model that leverages learned shape
    priors to produce a textured mesh without manual modelling. Three image to-3D
    platforms (Hitem3D, Hyper3D and Hunyuan3D 3.1) are compared on identical isometric
    inputs and assessed on architectural boundary clarity. We demonstrate GT through
    two applied cases: (i) reconstruction of ordinary residential streets in Detmold
    as stimuli for a virtual-reality study of multi sensory urban perception, and
    (ii) Green Editor, a design-exploration tool in which façade greenery is added
    or removed at the image layer before mesh generation.\r\nTogether these cases
    position Generative Twins as a scalable pathway for the digitization of ordinary
    building stock, with emphasis on controllability, editability, and iterative design
    workflows.@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Mohamed Khaled
      foaf_name: Ashmawy, Mohamed Khaled
      foaf_surname: Ashmawy
      foaf_workInfoHomepage: http://www.librecat.org/personId=81286
  - foaf_Person:
      foaf_givenName: Buse
      foaf_name: Akay, Buse
      foaf_surname: Akay
      foaf_workInfoHomepage: http://www.librecat.org/personId=88405
  - foaf_Person:
      foaf_givenName: Alvaro
      foaf_name: Balderrama, Alvaro
      foaf_surname: Balderrama
      foaf_workInfoHomepage: http://www.librecat.org/personId=74171
    orcid: 0000-0002-4118-2838
  bibo_doi: 10.52842/conf.ecaade.2026.1.619
  bibo_volume: 1
  dct_date: 2026^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/2684-1843
  dct_language: eng
  dct_publisher: eCAADe@
  dct_subject:
  - Digital Twins
  - Virtual Reality (VR
  - Artificial Intelligence (AI)
  - Image-to-3D
  - Generative Design.
  dct_title: 'Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction
    to Probabilistic Synthesis@'
...