[{"status":"public","publisher":"eCAADe","volume":1,"keyword":["Digital Twins","Virtual Reality (VR","Artificial Intelligence (AI)","Image-to-3D","Generative Design."],"conference":{"start_date":"2026-09-07","end_date":"2026-09-11","location":"Lübeck","name":"44. eCAADe-Konferenz"},"publication_status":"published","_id":"14070","publication":"eCAADe proceedings","date_updated":"2026-10-01T14:28:23Z","citation":{"havard":"M.K. Ashmawy, B. Akay, A. Balderrama, Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis, eCAADe, 2026.","chicago":"Ashmawy, Mohamed Khaled, Buse Akay, and Alvaro Balderrama. <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. <i>ECAADe Proceedings</i>. Vol. 1. eCAADe, 2026. <a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">https://doi.org/10.52842/conf.ecaade.2026.1.619</a>.","ama":"Ashmawy MK, Akay B, Balderrama A. <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. Vol 1. eCAADe; 2026. doi:<a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">10.52842/conf.ecaade.2026.1.619</a>","short":"M.K. Ashmawy, B. Akay, A. Balderrama, Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis, eCAADe, 2026.","mla":"Ashmawy, Mohamed Khaled, et al. “Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis.” <i>ECAADe Proceedings</i>, vol. 1, eCAADe, 2026, <a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">https://doi.org/10.52842/conf.ecaade.2026.1.619</a>.","chicago-de":"Ashmawy, Mohamed Khaled, Buse Akay und Alvaro Balderrama. 2026. <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. <i>eCAADe proceedings</i>. Bd. 1. eCAADe. doi:<a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">10.52842/conf.ecaade.2026.1.619</a>, .","apa":"Ashmawy, M. K., Akay, B., &#38; Balderrama, A. (2026). Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis. In <i>eCAADe proceedings</i> (Vol. 1). eCAADe. <a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">https://doi.org/10.52842/conf.ecaade.2026.1.619</a>","ieee":"M. K. Ashmawy, B. Akay, and A. Balderrama, <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>, vol. 1. eCAADe, 2026. doi: <a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">10.52842/conf.ecaade.2026.1.619</a>.","van":"Ashmawy MK, Akay B, Balderrama A. Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis. Vol. 1, eCAADe proceedings. eCAADe; 2026.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Ashmawy, Mohamed Khaled</span> ; <span style=\"font-variant:small-caps;\">Akay, Buse</span> ; <span style=\"font-variant:small-caps;\">Balderrama, Alvaro</span>: <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. Bd. 1 : eCAADe, 2026","ufg":"<b>Ashmawy, Mohamed Khaled/Akay, Buse/Balderrama, Alvaro</b>: Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis, Bd. 1, o. O. 2026.","bjps":"<b>Ashmawy MK, Akay B and Balderrama A</b> (2026) <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. eCAADe."},"year":"2026","type":"conference_editor_article","date_created":"2026-09-30T10:14:15Z","publication_identifier":{"issn":["2684-1843"]},"author":[{"id":"81286","full_name":"Ashmawy, Mohamed Khaled","first_name":"Mohamed Khaled","last_name":"Ashmawy"},{"full_name":"Akay, Buse","id":"88405","last_name":"Akay","first_name":"Buse"},{"orcid":"0000-0002-4118-2838","last_name":"Balderrama","first_name":"Alvaro","id":"74171","full_name":"Balderrama, Alvaro"}],"department":[{"_id":"DEP1634"}],"user_id":"83781","intvolume":"         1","language":[{"iso":"eng"}],"abstract":[{"text":"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.","lang":"eng"}],"title":"Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis","doi":"10.52842/conf.ecaade.2026.1.619"},{"publication":"Procedia Computer Science","main_file_link":[{"open_access":"1","url":"https://www.sciencedirect.com/science/article/pii/S1877050922024024"}],"date_updated":"2023-03-15T13:50:17Z","citation":{"ama":"Herrmann J-P, Atanasyan A, Casser F, Tackenberg S. A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems. <i>Procedia Computer Science</i>. 2023;217:1188-1199. doi:<a href=\"https://doi.org/10.1016/j.procs.2022.12.317\">https://doi.org/10.1016/j.procs.2022.12.317</a>","havard":"J.-P. Herrmann, A. Atanasyan, F. Casser, S. Tackenberg, A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems, Procedia Computer Science. 217 (2023) 1188–199.","short":"J.-P. Herrmann, A. Atanasyan, F. Casser, S. Tackenberg, Procedia Computer Science 217 (2023) 1188–199.","chicago":"Herrmann, Jan-Phillip, Alexander Atanasyan, Felix Casser, and Sven Tackenberg. “A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems.” <i>Procedia Computer Science</i> 217 (2023): 1188–99. <a href=\"https://doi.org/10.1016/j.procs.2022.12.317\">https://doi.org/10.1016/j.procs.2022.12.317</a>.","chicago-de":"Herrmann, Jan-Phillip, Alexander Atanasyan, Felix Casser und Sven Tackenberg. 2023. A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems. <i>Procedia Computer Science</i> 217: 1188–199. doi:<a href=\"https://doi.org/10.1016/j.procs.2022.12.317,\">https://doi.org/10.1016/j.procs.2022.12.317,</a> .","mla":"Herrmann, Jan-Phillip, et al. “A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems.” <i>Procedia Computer Science</i>, vol. 217, Elsevier, 2023, pp. 1188–99, doi:<a href=\"https://doi.org/10.1016/j.procs.2022.12.317\">https://doi.org/10.1016/j.procs.2022.12.317</a>.","apa":"Herrmann, J.-P., Atanasyan, A., Casser, F., &#38; Tackenberg, S. (2023). A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems. <i>Procedia Computer Science</i>, <i>217</i>, 1188–1199. <a href=\"https://doi.org/10.1016/j.procs.2022.12.317\">https://doi.org/10.1016/j.procs.2022.12.317</a>","din1505-2-1":"<span style=\"font-variant:small-caps;\">Herrmann, Jan-Phillip</span> ; <span style=\"font-variant:small-caps;\">Atanasyan, Alexander</span> ; <span style=\"font-variant:small-caps;\">Casser, Felix</span> ; <span style=\"font-variant:small-caps;\">Tackenberg, Sven</span>: A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems. In: <i>Procedia Computer Science</i> Bd. 217. Amsterdam, Elsevier (2023), S. 1188–199","bjps":"<b>Herrmann J-P <i>et al.</i></b> (2023) A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems. <i>Procedia Computer Science</i> <b>217</b>, 1188–1199.","ufg":"<b>Herrmann, Jan-Phillip et. al. (2023)</b>: A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems, in: <i>Procedia Computer Science</i> <i>217</i>, S. 1188–199.","ieee":"J.-P. Herrmann, A. Atanasyan, F. Casser, and S. Tackenberg, “A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems,” <i>Procedia Computer Science</i>, vol. 217, pp. 1188–199, 2023.","van":"Herrmann J-P, Atanasyan A, Casser F, Tackenberg S. A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems. Procedia Computer Science. 2023;217:1188–99."},"year":2023,"date_created":"2023-01-25T13:18:36Z","type":"scientific_journal_article","quality_controlled":"1","status":"public","publisher":"Elsevier","volume":217,"publication_status":"published","article_type":"original","keyword":["Colored Petri net","Human-centered Assistance","Experimentable Digital Twins"],"conference":{"start_date":"02.11.2022","end_date":"04.11.2022","name":"4th International Conference on Industry 4.0 and Smart Manufacturing","location":"Österreich"},"_id":"9358","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Real-time human-centered assistance in industrial processes depends on the individual history of the work person’s activities in the work system and requires adequate methods for tracking the person’s actions. Most research in human activity recognition is based on recognizing actions from video data using computer vision methods. Digital equipment, standardized machine data interfaces, and smart wearable devices extend the possibilities to describe the current state of the work system. Petri nets have already been applied to human activity recognition, however, without the requirement of detecting actions in real-time. This paper proposes a Petri net architecture that enables hierarchical description-based human activity recognition in industrial work processes. We present an extension, a Partitioned Colored Petri Net, based on the colored Petri net formalism that infers activities from state transitions of the work system in real-time. In a case study, we demonstrate the Petri net’s application for an error-based learning system that visualizes error consequences in augmented reality using experimentable digital twins."}],"title":"A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems","doi":"https://doi.org/10.1016/j.procs.2022.12.317","publication_identifier":{"issn":["1877-0509"]},"page":"1188-199","place":"Amsterdam","oa":"1","author":[{"last_name":"Herrmann","first_name":"Jan-Phillip","id":"75846","full_name":"Herrmann, Jan-Phillip"},{"full_name":"Atanasyan, Alexander","last_name":"Atanasyan","first_name":"Alexander"},{"full_name":"Casser, Felix","last_name":"Casser","first_name":"Felix"},{"first_name":"Sven","last_name":"Tackenberg","full_name":"Tackenberg, Sven","id":"71470"}],"department":[{"_id":"DEP7020"}],"user_id":"15514","intvolume":"       217"}]