[ { "id": "rasoulzadeh-2025-archcomplete", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/227557", "title": "ArchComplete: Autoregressive 3D architectural design generation with hierarchical diffusion-based upsampling", "date": "2025-12", "abstract": "Recent advances in 3D generative models have shown promising results but often fall short in capturing the complexity of architectural geometries and topologies. To tackle this, we present ArchComplete, a two-stage voxel-based 3D generative pipeline consisting of a vector-quantized model, whose composition is modeled with an autoregressive transformer for generating coarse shapes, followed by a set of multiscale diffusion models for augmenting with fine geometric details. Key to our pipeline is (i) learning a contextually rich codebook of local patch embeddings, optimized alongside a 2.5D perceptual loss that captures global spatial correspondence of projections onto three axis-aligned orthogonal planes, and (ii) redefining upsampling as a set of multiscale conditional diffusion models learning over a hierarchy of coarse-to-fine local volumetric patches, with a guided denoising process using 3D Gaussian windows that smooths noise estimates across overlapping patches during inference. Trained on our introduced dataset of 3D house models, ArchComplete autoregressively generates models at the resolution of (Formula presented) and progressively refines them up to (Formula presented), with voxel sizes as small as (Formula presented). ArchComplete solves a variety of tasks, including genetic interpolation and variation, unconditional synthesis, shape and plan-drawing completion, as well as geometric detailization, while achieving state-of-the-art performance.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5233, "drupal_id": 2334, "orcid_id": "0000-0002-0019-0137", "website": "https://www.cg.tuwien.ac.at/staff/ShervinRasoulzadeh", "firstname": "Shervin", "lastname": "Rasoulzadeh", "searchname": "Shervin Rasoulzadeh", "is_teacher": false, "name": "Shervin Rasoulzadeh", "publications": [ "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2023-ani", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "reisinger-2023-iad" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "rasoulzadeh-2022-strokes2surface", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5233", "__class": "Author" }, { "id": 5594, "drupal_id": null, "orcid_id": "0000-0003-3601-7907", "website": null, "firstname": "Mathias Bank", "lastname": "Stigsen", "searchname": "Mathias Bank Stigsen", "is_teacher": false, "name": "Mathias Bank Stigsen", "publications": [ "rasoulzadeh-2025-archcomplete" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5594", "__class": "Author" }, { "id": 1799, "drupal_id": null, "orcid_id": "0000-0002-0303-3284", "website": null, "firstname": "Iva", "lastname": "Kovacic", "searchname": "Iva Kovacic", "is_teacher": false, "name": "Iva Kovacic", "publications": [ "Honic_2021", "honic-2020-w78", "Kan_Peter-2021-BuildingMonitoring", "podkosova_2022_bimflexi-vr", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2023-ani", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "Reisinger_Julia-2021-parametricscript", "Reisinger-2021-JOBE", "reisinger-2023-iad", "stauss-2025-gfd", "wimmer-2022-acd" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "stauss-2025-gfd", "field_id": "lecturer", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1799", "__class": "Author" }, { "id": 5203, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Kristina", "lastname": "Schinegger", "searchname": "Kristina Schinegger", "is_teacher": false, "name": "Kristina Schinegger", "publications": [ "rasoulzadeh-2025-archcomplete", "wimmer-2022-acd" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5203", "__class": "Author" }, { "id": 5204, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Stefan", "lastname": "Rutzinger", 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{ "publ_id": "Zezulka-2025-NRL", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Zezulka-2026-FGTS", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Zezulka-2026-GridThermalSim", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "zhang-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ZL_2011_IVIG", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "zsolnai-feher-thesis-2019", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=193", "__class": "Author" } ], "articleno": "104477", "doi": "10.1016/j.cag.2025.104477", "issn": "1873-7684", "journal": "COMPUTERS & GRAPHICS-UK", "pages": "12", "publisher": "PERGAMON-ELSEVIER SCIENCE LTD", "volume": "133", "research_areas": [], "keywords": [ "Architectural Geometries", "Geometric Deep Learning", "Multiresolution Modeling", "Shape Analysis and Synthesis", "Shape Modeling Applications" ], "weblinks": [], "files": [], "projects_workgroups": [ { "id": "d4314", "workgroup_id": "rend", "drupal_id": 4314, "drupal_path": "/research/projects/ACD", "name": "Advanced Computational Design", "name_de": "Advanced Computational Design", "short_title": "ACD", "website": "http://acd.tuwien.ac.at", "status": "active", "short_abstract": null, "abstract": "

Research question: The main research question addressed by the SFB “Advanced Computational Design” is how to advance design tools and processes through multi- and interdisciplinary basic research in the areas of digital architecture, integrated building design, computer graphics and virtual reality, discrete and applied geometry, and computational mechanics. 

\n

Wider research context: Architecture, Engineering and Construction (AEC) shapes our built environment, exerting substantial environmental, cultural and economic influence on society. However, it is among the least digitized industries, still caught in silo-thinking and sequential planning processes. The Information and Communication Technology field, on the other hand, is highly innovative, creating digital design tools that are well-founded in basic research, but often lack relevant domain knowledge, thus hardly meeting designers’ needs.

\n

Innovation: We will connect architecture, computer science, mathematics and engineering in order to develop advanced computational design tools able to incorporate implicit and explicit design knowledge. This unique combination of scientific disciplines and collaborative research with strong theoretical foundations aims to bring radical innovation in computational design by allowing immediate feedback already in early design phases and by expanding solution spaces by computing design variants that cannot be found by current methods.

\n

Approach: The proposed research is structured in three areas: Design Methodology (A1), Visual and Haptic Design Interaction (A2) and Form Finding (A3). A1 uses ontologies to describe AEC design semantics, coupled to a novel digital mixed-reality sketchbook, and an innovative implicit modeling approach based on retrieving and enhancing 2D images and 3D point clouds through transfer learning. A1 also acts as a platform for integrating and evaluating the computational tools and methods developed in A2 and A3. These areas will investigate research questions in computational design involving algorithmic solutions. A2 investigates real-time global-illumination and optimization algorithms for lighting design, as well as a new method for large-scale haptic interactions in virtual reality based on a mobile robotic platform. In A3, form finding will be explored regarding geometric, mechanical and material constraints, in particular: paneling of complex shapes by patches of certain surface classes while optimizing the number of molds; algorithms for finding new transformable quad-surfaces; mechanical models for an efficient simulation of bio-composite material systems. Furthermore, new ways of form-finding will be explored experimentally, which will allow for validating the developed algorithmic approaches and reconsidering model assumptions and constraints.

\n

Added value: The fundamental computational tools and methods to be developed will be applicable in AEC and other fields of the creative industries.

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The input to our pipeline consists of 3D strokes' polyline vertices and their timestamps as the 4th dimension, along with additional metadata recorded throughout sketching. Inspired by architectural sketching practices, our pipeline combines a classifier and two clustering models to achieve its goal. First, with a set of extracted hand-engineered features from the sketch, the classifier recognizes the type of individual strokes between those depicting boundaries (Shape strokes) and those depicting enclosed areas (Scribble strokes). Next, the two clustering models parse strokes of each type into distinct groups, each representing an individual edge or face of the intended architectural object. Curve networks are then formed through topology recovery of consolidated Shape clusters and surfaced using Scribble clusters guiding the cycle discovery. 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Research question: The main research question addressed by the SFB “Advanced Computational Design” is how to advance design tools and processes through multi- and interdisciplinary basic research in the areas of digital architecture, integrated building design, computer graphics and virtual reality, discrete and applied geometry, and computational mechanics. 

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Wider research context: Architecture, Engineering and Construction (AEC) shapes our built environment, exerting substantial environmental, cultural and economic influence on society. However, it is among the least digitized industries, still caught in silo-thinking and sequential planning processes. The Information and Communication Technology field, on the other hand, is highly innovative, creating digital design tools that are well-founded in basic research, but often lack relevant domain knowledge, thus hardly meeting designers’ needs.

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Innovation: We will connect architecture, computer science, mathematics and engineering in order to develop advanced computational design tools able to incorporate implicit and explicit design knowledge. This unique combination of scientific disciplines and collaborative research with strong theoretical foundations aims to bring radical innovation in computational design by allowing immediate feedback already in early design phases and by expanding solution spaces by computing design variants that cannot be found by current methods.

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Approach: The proposed research is structured in three areas: Design Methodology (A1), Visual and Haptic Design Interaction (A2) and Form Finding (A3). A1 uses ontologies to describe AEC design semantics, coupled to a novel digital mixed-reality sketchbook, and an innovative implicit modeling approach based on retrieving and enhancing 2D images and 3D point clouds through transfer learning. A1 also acts as a platform for integrating and evaluating the computational tools and methods developed in A2 and A3. These areas will investigate research questions in computational design involving algorithmic solutions. A2 investigates real-time global-illumination and optimization algorithms for lighting design, as well as a new method for large-scale haptic interactions in virtual reality based on a mobile robotic platform. In A3, form finding will be explored regarding geometric, mechanical and material constraints, in particular: paneling of complex shapes by patches of certain surface classes while optimizing the number of molds; algorithms for finding new transformable quad-surfaces; mechanical models for an efficient simulation of bio-composite material systems. Furthermore, new ways of form-finding will be explored experimentally, which will allow for validating the developed algorithmic approaches and reconsidering model assumptions and constraints.

\n

Added value: The fundamental computational tools and methods to be developed will be applicable in AEC and other fields of the creative industries.

", "start_date": "2020-03-01", "end_date": "2028-02-29", "leader_id": 193, "logo": null, "funding_organisations": [], "research_areas": [], "publications": [ "Derflinger-2026-RTTW2", "ecormier-nocca-2025-sls", "Erhardt_2025_Scutes", "Erhardt_Seirlehner-2024-TamashiiIntegration", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "Fuericht-2026-FPD", "Grisenti-2026-HSHPG", "huber-2025-esl", "koenigsberger-2024-msu", "Koeppl-2023-DLO", "kovacs-2023-ttm", "landauer-2022-kido", "LIPP-2020-PHD", "lipp-2024-val", "Meier_2024_WIALT", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Preymann-2022-pytamashii", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "reisinger-2023-iad", "Schwengerer_Mathias-2022-BGL", "steinkellner-2022-dll", "ulschmid-2024-reo", "ulschmid-2025-apc", "unterguggenberger-2023-vaw", "wimmer-2022-acd", "wimmer-2023-acd", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang-thesis" ], "url": "https://www.cg.tuwien.ac.at/research/projects/ACD", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/rasoulzadeh-2024-strokes2surface/", "__class": "Publication" }, { "id": "reisinger-2023-iad", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/188467", "title": "Integrating AEC Domain-Specific Multidisciplinary Knowledge for Informed and Interactive Feedback in Early Design Stages", "date": "2023-10", "abstract": "In the context of digitalization in the industry, a variety of technologies has been developed for system integration and enhanced team collaboration in the Architecture, Engineering and Construction (AEC) industry. Multidisciplinary design requirements are characterized by a high degree of complexity. Early design methods often rely on implicit or experiential design knowledge, whereas contemporary digital design tools mostly reflect domain-specific silo thinking with time-consuming iterative design processes. Yet, the early design stages hold the greatest potential for design optimization. This paper presents a framework of a multidisciplinary computational integration platform for early design stages that enables integration of AEC domain-specific methods from architecture, engineering, mathematics and computer science. The platform couples a semantic integrative mixed reality sketching application to a shape inference machine-learning based algorithm to link methods for different computation, simulation and digital fabrication tasks. A proof of concept of the proposed framework is presented for the use case of a freeform geometry wall. Future research will explore the potential of the framework to be extended to larger building projects with the aim to connect the method into BIM-processes.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "date", "repositum_presentation_id": null, "authors": [ { "id": 1874, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Julia", "lastname": "Reisinger", "searchname": "Julia Reisinger", "is_teacher": false, "name": "Julia Reisinger", "publications": [ "podkosova_2022_bimflexi-vr", "rasoulzadeh-2023-ani", "Reisinger_Julia-2021-parametricscript", "Reisinger-2021-JOBE", "reisinger-2023-iad" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "reisinger-2023-iad", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1874", "__class": "Author" }, { "id": 5233, "drupal_id": 2334, "orcid_id": "0000-0002-0019-0137", "website": "https://www.cg.tuwien.ac.at/staff/ShervinRasoulzadeh", "firstname": "Shervin", "lastname": "Rasoulzadeh", "searchname": "Shervin Rasoulzadeh", "is_teacher": false, "name": "Shervin Rasoulzadeh", "publications": [ "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2023-ani", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "reisinger-2023-iad" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "rasoulzadeh-2022-strokes2surface", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5233", "__class": "Author" }, { "id": 1487, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Bálint Istvan", "lastname": "Kovács", "searchname": "Bálint Istvan Kovács", "is_teacher": false, "name": "Bálint Istvan Kovács", "publications": [ "Kovacs_2017", "Kovacs_2020", "kovacs-2023-ttm", "reisinger-2023-iad", "Vasylevska2020VRB" ], "publications_first": 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Research question: The main research question addressed by the SFB “Advanced Computational Design” is how to advance design tools and processes through multi- and interdisciplinary basic research in the areas of digital architecture, integrated building design, computer graphics and virtual reality, discrete and applied geometry, and computational mechanics. 

\n

Wider research context: Architecture, Engineering and Construction (AEC) shapes our built environment, exerting substantial environmental, cultural and economic influence on society. However, it is among the least digitized industries, still caught in silo-thinking and sequential planning processes. The Information and Communication Technology field, on the other hand, is highly innovative, creating digital design tools that are well-founded in basic research, but often lack relevant domain knowledge, thus hardly meeting designers’ needs.

\n

Innovation: We will connect architecture, computer science, mathematics and engineering in order to develop advanced computational design tools able to incorporate implicit and explicit design knowledge. This unique combination of scientific disciplines and collaborative research with strong theoretical foundations aims to bring radical innovation in computational design by allowing immediate feedback already in early design phases and by expanding solution spaces by computing design variants that cannot be found by current methods.

\n

Approach: The proposed research is structured in three areas: Design Methodology (A1), Visual and Haptic Design Interaction (A2) and Form Finding (A3). A1 uses ontologies to describe AEC design semantics, coupled to a novel digital mixed-reality sketchbook, and an innovative implicit modeling approach based on retrieving and enhancing 2D images and 3D point clouds through transfer learning. A1 also acts as a platform for integrating and evaluating the computational tools and methods developed in A2 and A3. These areas will investigate research questions in computational design involving algorithmic solutions. A2 investigates real-time global-illumination and optimization algorithms for lighting design, as well as a new method for large-scale haptic interactions in virtual reality based on a mobile robotic platform. In A3, form finding will be explored regarding geometric, mechanical and material constraints, in particular: paneling of complex shapes by patches of certain surface classes while optimizing the number of molds; algorithms for finding new transformable quad-surfaces; mechanical models for an efficient simulation of bio-composite material systems. Furthermore, new ways of form-finding will be explored experimentally, which will allow for validating the developed algorithmic approaches and reconsidering model assumptions and constraints.

\n

Added value: The fundamental computational tools and methods to be developed will be applicable in AEC and other fields of the creative industries.

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Digital design tools in this domain often lack proper communication between different stages of design and relevant domain knowledge. Furthermore, decisions made in the early stages of design, where sketching is used to initiate, develop, and communicate ideas, heavily impact later stages, resulting in the need for rapid feedback to the architectural designer so they can proceed with adequate knowledge about design implications. Accordingly, this paper presents research on a novel integrative design framework based on a recently developed 4D sketching interface, targeted for architectural design as a form-finding tool coupled with three modules: (1) a Geometric Modelling module, which utilises Points2Surf as a machine learning model for automatic surface mesh reconstruction from the point clouds produced by sketches, (2) a Material Modelling module, which predicts the mechanical properties of biocomposites based on multiscale micromechanics homogenisation techniques, and (3) a Structural Analysis module, which assesses the mechanical performance of the meshed structure on the basis of the predicted material properties using finite element simulations. The proposed framework is a step towards using material-informed design already in the early stages of design.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5233, "drupal_id": 2334, "orcid_id": "0000-0002-0019-0137", "website": "https://www.cg.tuwien.ac.at/staff/ShervinRasoulzadeh", "firstname": "Shervin", "lastname": "Rasoulzadeh", "searchname": "Shervin Rasoulzadeh", "is_teacher": false, "name": "Shervin Rasoulzadeh", "publications": [ "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2023-ani", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "reisinger-2023-iad" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "rasoulzadeh-2022-strokes2surface", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5233", "__class": "Author" }, { "id": 5303, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "V.", "lastname": "Senk", "searchname": "V. 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Research question: The main research question addressed by the SFB “Advanced Computational Design” is how to advance design tools and processes through multi- and interdisciplinary basic research in the areas of digital architecture, integrated building design, computer graphics and virtual reality, discrete and applied geometry, and computational mechanics. 

\n

Wider research context: Architecture, Engineering and Construction (AEC) shapes our built environment, exerting substantial environmental, cultural and economic influence on society. However, it is among the least digitized industries, still caught in silo-thinking and sequential planning processes. The Information and Communication Technology field, on the other hand, is highly innovative, creating digital design tools that are well-founded in basic research, but often lack relevant domain knowledge, thus hardly meeting designers’ needs.

\n

Innovation: We will connect architecture, computer science, mathematics and engineering in order to develop advanced computational design tools able to incorporate implicit and explicit design knowledge. This unique combination of scientific disciplines and collaborative research with strong theoretical foundations aims to bring radical innovation in computational design by allowing immediate feedback already in early design phases and by expanding solution spaces by computing design variants that cannot be found by current methods.

\n

Approach: The proposed research is structured in three areas: Design Methodology (A1), Visual and Haptic Design Interaction (A2) and Form Finding (A3). A1 uses ontologies to describe AEC design semantics, coupled to a novel digital mixed-reality sketchbook, and an innovative implicit modeling approach based on retrieving and enhancing 2D images and 3D point clouds through transfer learning. A1 also acts as a platform for integrating and evaluating the computational tools and methods developed in A2 and A3. These areas will investigate research questions in computational design involving algorithmic solutions. A2 investigates real-time global-illumination and optimization algorithms for lighting design, as well as a new method for large-scale haptic interactions in virtual reality based on a mobile robotic platform. In A3, form finding will be explored regarding geometric, mechanical and material constraints, in particular: paneling of complex shapes by patches of certain surface classes while optimizing the number of molds; algorithms for finding new transformable quad-surfaces; mechanical models for an efficient simulation of bio-composite material systems. Furthermore, new ways of form-finding will be explored experimentally, which will allow for validating the developed algorithmic approaches and reconsidering model assumptions and constraints.

\n

Added value: The fundamental computational tools and methods to be developed will be applicable in AEC and other fields of the creative industries.

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