{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T13:17:08Z","timestamp":1781529428837,"version":"3.54.1"},"reference-count":43,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2020,5,13]],"date-time":"2020-05-13T00:00:00Z","timestamp":1589328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>In recent years, advances in computer hardware, graphics rendering algorithms and computer vision have enabled the utilization of 3D building reconstructions in the fields of archeological structure restoration and urban planning. This paper deals with the reconstruction of realistic 3D models of buildings fa\u00e7ades, in the urban environment for cultural heritage. The proposed approach is an extension of our previous work in this research topic, which introduced a methodology for accurate 3D realistic fa\u00e7ade reconstruction by defining and exploiting a relation between stereoscopic image and tacheometry data. In this work, we re-purpose well known deep neural network architectures in the fields of image segmentation and single image depth prediction, for the tasks of fa\u00e7ade structural element detection, depth point-cloud generation and protrusion estimation, with the goal of alleviating drawbacks in our previous design, resulting in a more light-weight, robust, flexible and cost-effective design.<\/jats:p>","DOI":"10.3390\/ijgi9050322","type":"journal-article","created":{"date-parts":[[2020,5,14]],"date-time":"2020-05-14T02:55:41Z","timestamp":1589424941000},"page":"322","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["3D Building Fa\u00e7ade Reconstruction Using Deep Learning"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3867-7119","authenticated-orcid":false,"given":"Konstantinos","family":"Bacharidis","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Crete, 70013 Heraklion, Greece"},{"name":"Foundation of Research and Technology Hellas (FORTH), 70013 Heraklion, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Froso","family":"Sarri","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Technical University of Crete, 73100 Chania, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lemonia","family":"Ragia","sequence":"additional","affiliation":[{"name":"ATHENA Research and Innovation Information Technologies, 15125 Marousi, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4525","DOI":"10.3390\/s90604525","article-title":"Building Facade Reconstruction by Fusing Terrestrial Laser Points and Images","volume":"9","author":"Pu","year":"2009","journal-title":"Sensors"},{"key":"ref_2","unstructured":"Abmayr, T., H\u00e4rtl, F., Reink\u00f6ster, M., and Fr\u00f6hlich, C. (2005, January 22\u201324). Terrestrial Laser Scanning: Applications in Cultural Heritage Conservation and Civil Engineering. Proceedings of the ISPRS Working Group V4, Mestre-Venice, Italy."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ma\u2019arof, I., Bahari, S.Z., Latif, Z.A., Sulaiman, N.A., and Samad, A.M. (December, January 29). Image based modeling and documentation of Malaysian historical monuments using Digital Close-Range Photogrammetry (DCRP). Proceedings of the 2013 IEEE International Conference on Control System, Computing and Engineering, Penang, Malaysia.","DOI":"10.1109\/ICCSCE.2013.6720002"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1179\/1743131X14Y.0000000077","article-title":"Close-range photogrammetry applied to the documentation of cultural heritage using telescopic and wide-angle lenses","volume":"62","author":"Reinoso","year":"2014","journal-title":"Imaging Sci. J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1016\/j.autcon.2010.06.007","article-title":"Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques","volume":"19","author":"Tang","year":"2010","journal-title":"Autom. Constr."},{"key":"ref_6","unstructured":"Becker, S., and Haala, N. (2007, January 12\u201314). Combined feature extraction for fa\u00e7ade reconstruction. Proceedings of the ISPRS Workshop Laser Scanning, Espoo, Finland."},{"key":"ref_7","first-page":"1","article-title":"3D model of al zubarah fortress in qatar - terrestrial laser scanning vs. dense image matching","volume":"XL-5\/W4","author":"Kersten","year":"2015","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_8","unstructured":"Dellaert, F., Seitz, S.M., Thorpe, C.E., and Thrun, S. (2000, January 15). Structure from motion without correspondence. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2000), Hilton Head Island, SC, USA."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Luhmann, T., Robson, S., Kyle, S., and Boehm, J. (2013). Close-Range Photogrammetry and 3D Imaging, Walter de Gruyter.","DOI":"10.1515\/9783110302783"},{"key":"ref_10","first-page":"339","article-title":"Virtual Reality Model of the Northern Sluice of the Ancient Dam in Marib\/Yemen by Combination of Digital Photogrammetry and Terrestrial Laser Scanning for Archaeological Applications","volume":"5","author":"Kersten","year":"2007","journal-title":"Int. J. Archit. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"133","DOI":"10.5194\/isprsarchives-XL-5-W1-133-2013","article-title":"The combination of laser scanning and structure from motion technology for creation of accurate exterior and interior orthophotos of St. Nicholas Baroque church","volume":"40","author":"Koska","year":"2013","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_12","unstructured":"Fritsch, D., Becker, S., and Rothermel, M. (2013, January 3\u20134). Modeling facade structures using point clouds from dense image matching. Proceedings of the Intl. Conf. on Advances in Civil, Structural and Mechanical Engineering, Hong Kong, China."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"29","DOI":"10.3389\/fict.2018.00029","article-title":"Automatic 3D Reconstruction from Unstructured Videos Combining Video Summarization and Structure from Motion","volume":"5","author":"Doulamis","year":"2018","journal-title":"Front. ICT"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Paravolidakis, V., Bacharidis, K., Sarri, F., Ragia, L., and Zervakis, M. (2016, January 4\u20136). Reduction of building fa\u00e7ade model complexity using computer vision. Proceedings of the 2016 IEEE International Conference on Imaging Systems and Techniques (IST), Chania, Greece.","DOI":"10.1109\/IST.2016.7738269"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1016\/j.autcon.2018.10.007","article-title":"Automatic window detection in facade images","volume":"96","author":"Neuhausen","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Salberg, A.B., Hardeberg, J.Y., and Jenssen, R. (2009). Extraction of Windows in Facade Using Kernel on Graph of Contours. Image Analysis, Springer.","DOI":"10.1007\/978-3-642-02230-2"},{"key":"ref_17","first-page":"709","article-title":"A convolutional network for semantic facade segmentation and interpretation","volume":"XLI-B3","author":"Schmitz","year":"2016","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Fathalla, R., and Vogiatzis, G. (2017, January 4\u20137). A deep learning pipeline for semantic facade segmentation. Proceedings of the British Machine Vision Conference 2017 (BMVC), London, UK.","DOI":"10.5244\/C.31.120"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Liu, H., Zhang, J., Zhu, J., and Hoi, S.C.H. (2017, January 19\u201325). DeepFacade: A Deep Learning Approach to Facade Parsing. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne, Australia.","DOI":"10.24963\/ijcai.2017\/320"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Bacharidis, K., Sarri, F., Paravolidakis, V., Ragia, L., and Zervakis, M. (2018). Fusing Georeferenced and Stereoscopic Image Data for 3D Building Fa\u00e7ade Reconstruction. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7040151"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Laina, I., Rupprecht, C., Belagiannis, V., Tombari, F., and Navab, N. (2016, January 25\u201328). Deeper depth prediction with fully convolutional residual networks. Proceedings of the IEEE 2016 Fourth International Conference on 3D Vision (3DV), Stanford, CA, USA.","DOI":"10.1109\/3DV.2016.32"},{"key":"ref_22","unstructured":"Ren, H., El-khamy, M., and Lee, J. (2019). Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding. arXiv."},{"key":"ref_23","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J. (July, January 26). Deep residual learning for image recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1090\/conm\/443\/08555","article-title":"A robust hybrid of lasso and ridge regression","volume":"443","author":"Owen","year":"2007","journal-title":"Contemp. Math."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1007\/BF00133570","article-title":"Snakes: Active contour models","volume":"1","author":"Kass","year":"1988","journal-title":"Int. J. Comput. Vis."},{"key":"ref_26","unstructured":"Yu, F., and Koltun, V. (2020, May 12). Multi-Scale Context Aggregation by Dilated Convolutions, Available online: http:\/\/xxx.lanl.gov\/abs\/1511.07122."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1007\/s11263-015-0868-z","article-title":"ATLAS: A Three-Layered Approach to Facade Parsing","volume":"118","author":"Mathias","year":"2016","journal-title":"Int. J. Comput. Vis."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.Y., Zhou, T., and Efros, A.A. (2017, January 21\u201326). Image-to-Image Translation with Conditional Adversarial Networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref_29","unstructured":"Kor\u010d, F., and F\u00f6rstner, W. (2009). eTRIMS Image Database for Interpreting Images of Man-Made Scenes, University of Bonn. Technical Report, TR-IGG-P-2009-01."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Tyle\u010dek, R., and \u0160\u00e1ra, R. (2013). Spatial Pattern Templates for Recognition of Objects with Regular Structure. German Conference on Pattern Recognition, Springer.","DOI":"10.1007\/978-3-642-40602-7_39"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., and Girshick, R. (2017, January 22\u201329). Mask r-cnn. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1016\/j.robot.2008.08.005","article-title":"Towards 3D point cloud based object maps for household environments","volume":"56","author":"Rusu","year":"2008","journal-title":"Robot. Auton. Syst."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Gardiner, J.D., Behnsen, J., and Brassey, C.A. (2018). Alpha shapes: Determining 3D shape complexity across morphologically diverse structures. BMC Evol. Biol., 18.","DOI":"10.1186\/s12862-018-1305-z"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ragia, L., Sarri, F., and Mania, K. (2015, January 28\u201330). 3D reconstruction and visualization of alternatives for restoration of historic buildings: A new approach. Proceedings of the IEEE 2015 1st International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM), Barcelona, Spain.","DOI":"10.5220\/0005376700940102"},{"key":"ref_35","unstructured":"Frisch, D. (2020, March 03). Distance Between Point and Triangulated Surface. Available online: https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/52882-point2trimesh-distance-between-point-and-triangulated-surface."},{"key":"ref_36","first-page":"2","article-title":"Fast approximate nearest neighbors with automatic algorithm configuration","volume":"2","author":"Muja","year":"2009","journal-title":"VISAPP"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1109\/TPAMI.2008.132","article-title":"Make3d: Learning 3d scene structure from a single still image","volume":"31","author":"Saxena","year":"2008","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Hartley, R., and Zisserman, A. (2004). Multiple View Geometry in Computer Vision, Cambridge University Press. [2nd ed.].","DOI":"10.1017\/CBO9780511811685"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2487228.2487237","article-title":"Screened poisson surface reconstruction","volume":"32","author":"Kazhdan","year":"2013","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1017\/S0962492900001331","article-title":"Triangulations and meshes in computational geometry","volume":"9","author":"Edelsbrunner","year":"2000","journal-title":"Acta Numer."},{"key":"ref_41","first-page":"W10","article-title":"From point cloud to surface: The modeling and visualization problem","volume":"34","author":"Fabio","year":"2003","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s10109-018-0267-4","article-title":"Precise photorealistic visualization for restoration of historic buildings based on tacheometry data","volume":"20","author":"Ragia","year":"2018","journal-title":"J. Geogr. Syst."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"405","DOI":"10.5194\/isprs-archives-XLII-2-W3-405-2017","article-title":"First experiences with the Trimble SX10 Scanning Total Station for building facade survey","volume":"42","author":"Lachat","year":"2017","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/5\/322\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:28:29Z","timestamp":1760174909000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/5\/322"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,13]]},"references-count":43,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["ijgi9050322"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9050322","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,13]]}}}