{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T06:38:12Z","timestamp":1767854292431,"version":"3.49.0"},"publisher-location":"Cham","reference-count":92,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031732089","type":"print"},{"value":"9783031732096","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-73209-6_13","type":"book-chapter","created":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T15:02:57Z","timestamp":1730386977000},"page":"215-234","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["GroundUp: Rapid Sketch-Based 3D City Massing"],"prefix":"10.1007","author":[{"given":"Gizem Esra","family":"\u00dcnl\u00fc","sequence":"first","affiliation":[]},{"given":"Mohamed","family":"Sayed","sequence":"additional","affiliation":[]},{"given":"Yulia","family":"Gryaditskaya","sequence":"additional","affiliation":[]},{"given":"Gabriel","family":"Brostow","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,1]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"Benes, B., Zhou, X., Chang, P., Cani, M.P.R.: Urban brush: intuitive and controllable urban layout editing. In: The 34th Annual ACM Symposium on User Interface Software and Technology (2021)","DOI":"10.1145\/3472749.3474787"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Bhattacharjee, S., Chaudhuri, P.: A survey on sketch based content creation: from the desktop to virtual and augmented reality. Computer Graphics Forum 39, 757\u2013780 (05 2020)","DOI":"10.1111\/cgf.14024"},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Binninger, A., Hertz, A., Sorkine-Hornung, O., Cohen-Or, D., Giryes, R.: Sens: sketch-based implicit neural shape modeling. Arxiv preprint (2023)","DOI":"10.1111\/cgf.15015"},{"key":"13_CR4","doi-asserted-by":"crossref","unstructured":"Bonnici, A., et al.: Sketch-based interaction and modeling: where do we stand? Artif. Intell. Eng. Des. Anal. Manuf. 33, 1\u201319 (2019)","DOI":"10.1017\/S0890060419000349"},{"key":"13_CR5","unstructured":"Bozic, A., Palafox, P., Thies, J., Dai, A., Nie\u00dfner, M.: TransformerFusion: monocular RGB scene reconstruction using transformers. In: NeurIPS (2021)"},{"key":"13_CR6","doi-asserted-by":"crossref","DOI":"10.1016\/j.cad.2022.103283","volume":"150","author":"JD Camba","year":"2022","unstructured":"Camba, J.D., Company, P., Naya, F.: Sketch-based modeling in mechanical engineering design: current status and opportunities. Comput. Aided Des. 150, 103283 (2022)","journal-title":"Comput. Aided Des."},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Chen, S., Ogawa, Y., Zhao, C., Sekimoto, Y.: Large-scale individual building extraction from open-source satellite imagery via super-resolution-based instance segmentation approach. ISPRS J. Photogram. Remote Sens. 195 (2023)","DOI":"10.1016\/j.isprsjprs.2022.11.006"},{"key":"13_CR8","first-page":"1","volume":"61","author":"S Chen","year":"2023","unstructured":"Chen, S., Shi, Y., Xiong, Z., Zhu, X.X.: Htc-dc net: monocular height estimation from single remote sensing images. IEEE Trans. Geosci. Remote Sens. 61, 1\u201318 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"13_CR9","doi-asserted-by":"crossref","unstructured":"Chen, Z., et al.: Heightformer: a multilevel interaction and image-adaptive classification-regression network for monocular height estimation with aerial images. arXiv preprint arXiv:2310.07995 (2023)","DOI":"10.3390\/rs16020295"},{"key":"13_CR10","doi-asserted-by":"publisher","unstructured":"Cheng, Z., et al.: Cross-modal 3D shape generation and manipulation. In: Avidan, S., Brostow, G., Cisse, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022, pp. 303\u2013321. Springer, Heidelberg (2022). https:\/\/doi.org\/10.1007\/978-3-031-20062-5_18","DOI":"10.1007\/978-3-031-20062-5_18"},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Chowdhury, P.N., Wang, T., Ceylan, D., Song, Y.Z., Gryaditskaya, Y.: Garment ideation: iterative view-aware sketch-based garment modeling. In: 2022 International Conference on 3D Vision (3DV), pp. 22\u201331 (2022)","DOI":"10.1109\/3DV57658.2022.00015"},{"issue":"1","key":"13_CR12","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/0004-3702(71)90005-1","volume":"2","author":"MB Clowes","year":"1971","unstructured":"Clowes, M.B.: On seeing things. Artif. Intell. 2(1), 79\u2013116 (1971)","journal-title":"Artif. Intell."},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Collins, R.T.: A space-sweep approach to true multi-image matching. In: CVPR (1996)","DOI":"10.1109\/CVPR.1996.517097"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Delanoy, J., Aubry, M., Isola, P., Efros, A.A., Bousseau, A.: 3d sketching using multi-view deep volumetric prediction. Proc. ACM Comput. Graph. Interact. Tech. 1(1) (2018)","DOI":"10.1145\/3203197"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"13_CR16","unstructured":"Deng, J., et al.: Citygen: infinite and controllable 3d city layout generation. arXiv preprint arXiv:2312.01508 (2023)"},{"key":"13_CR17","unstructured":"Duan, Y., Zhu, Z., Guo, X.: Diffusiondepth: diffusion denoising approach for monocular depth estimation. CoRR arxiv:2303.05021 (2023)"},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Duzceker, A., Galliani, S., Vogel, C., Speciale, P., Dusmanu, M., Pollefeys, M.: Deepvideomvs: multi-view stereo on video with recurrent spatio-temporal fusion. In: CVPR (2021)","DOI":"10.1109\/CVPR46437.2021.01507"},{"key":"13_CR19","unstructured":"Eigen, D., Puhrsch, C., Fergus, R.: Depth map prediction from a single image using a multi-scale deep network. In: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, Montreal, Quebec, Canada, 8\u201313 December 2014, pp. 2366\u20132374 (2014)"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Feng, T., Fan, F., Bednarz, T.: A review of computer graphics approaches to urban modeling from a machine learning perspective. Front. Inf. Technol. Electron. Engi. 22(7) (2021)","DOI":"10.1631\/FITEE.2000141"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Fu, H., Gong, M., Wang, C., Batmanghelich, K., Tao, D.: Deep ordinal regression network for monocular depth estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2018)","DOI":"10.1109\/CVPR.2018.00214"},{"key":"13_CR22","doi-asserted-by":"crossref","unstructured":"Furukawa, Y., Hern\u00e1ndez, C., et\u00a0al.: Multi-view stereo: a tutorial. Found. Trends\u00ae Comput. Graph. Vision 9(1-2), 1\u2013148 (2015)","DOI":"10.1561\/0600000052"},{"key":"13_CR23","doi-asserted-by":"publisher","unstructured":"Gao, C., Yu, Q., Sheng, L., Song, Y., Xu, D.: Sketchsampler: sketch-based 3d reconstruction via view-dependent depth sampling. In: ECCV 2022, pp. 464\u2013479. Springer, Heidelberg (2022). https:\/\/doi.org\/10.1007\/978-3-031-19769-7_27","DOI":"10.1007\/978-3-031-19769-7_27"},{"key":"13_CR24","doi-asserted-by":"crossref","unstructured":"Ghamisi, P., Yokoya, N.: Img2dsm: height simulation from single imagery using conditional generative adversarial net. IEEE Geosci. Remote Sens. Lett. 15(5) (2018)","DOI":"10.1109\/LGRS.2018.2806945"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Godard, C., Aodha, O.M., Brostow, G.J.: Unsupervised monocular depth estimation with left-right consistency. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, 21\u201326 July 2017, pp. 6602\u20136611. IEEE Computer Society (2017)","DOI":"10.1109\/CVPR.2017.699"},{"key":"13_CR26","doi-asserted-by":"crossref","unstructured":"Godard, C., Aodha, O.M., Firman, M., Brostow, G.J.: Digging into self-supervised monocular depth estimation. In: 2019 IEEE\/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), 27 October\u20132 November 2019, pp. 3827\u20133837. IEEE (2019)","DOI":"10.1109\/ICCV.2019.00393"},{"key":"13_CR27","doi-asserted-by":"crossref","unstructured":"Godard, C., Mac\u00a0Aodha, O., Brostow, G.J.: Unsupervised monocular depth estimation with left-right consistency. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.699"},{"key":"13_CR28","unstructured":"Goesele, M., Curless, B., Seitz, S.M.: Multi-view stereo revisited. In: CVPR (2006)"},{"key":"13_CR29","doi-asserted-by":"crossref","unstructured":"Guillard, B., Remelli, E., Yvernay, P., Fua, P.: Sketch2mesh: reconstructing and editing 3d shapes from sketches. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (2021)","DOI":"10.1109\/ICCV48922.2021.01278"},{"key":"13_CR30","doi-asserted-by":"crossref","unstructured":"H\u00e4hnlein, F., Gryaditskaya, Y., Sheffer, A., Bousseau, A.: Symmetry-driven 3d reconstruction from concept sketches. In: ACM SIGGRAPH 2022 Conference Proceedings, pp.\u00a01\u20138 (2022)","DOI":"10.1145\/3528233.3530723"},{"key":"13_CR31","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"13_CR32","doi-asserted-by":"crossref","unstructured":"He, L., Aliaga, D.: Globalmapper: arbitrary-shaped urban layout generation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 454\u2013464 (2023)","DOI":"10.1109\/ICCV51070.2023.00048"},{"key":"13_CR33","first-page":"295","volume":"6","author":"DA Huffman","year":"1971","unstructured":"Huffman, D.A.: Impossible objects as nonsense sentences. Mach. Intell. 6, 295\u2013323 (1971)","journal-title":"Mach. Intell."},{"key":"13_CR34","doi-asserted-by":"crossref","DOI":"10.1002\/9781118879504","volume-title":"Drawing Architecture and the Urban","author":"S Jacoby","year":"2016","unstructured":"Jacoby, S.: Drawing Architecture and the Urban. Wiley, Hoboken (2016)"},{"key":"13_CR35","unstructured":"Kang, S.B., Szeliski, R., Chai, J.: Handling occlusions in dense multi-view stereo. In: CVPR (2001)"},{"key":"13_CR36","doi-asserted-by":"crossref","unstructured":"Ke, B., Obukhov, A., Huang, S., Metzger, N., Daudt, R.C., Schindler, K.: Repurposing diffusion-based image generators for monocular depth estimation. arXiv preprint arXiv:2312.02145 (2023)","DOI":"10.1109\/CVPR52733.2024.00907"},{"key":"13_CR37","doi-asserted-by":"crossref","unstructured":"Kelly, T., Femiani, J., Wonka, P., Mitra, N.J.: Bigsur: large-scale structured urban reconstruction. ACM Trans. Graph. 36(6) (2017)","DOI":"10.1145\/3130800.3130823"},{"key":"13_CR38","doi-asserted-by":"crossref","unstructured":"Kelly, T., Guerrero, P., Steed, A., Wonka, P., Mitra, N.J.: Frankengan: guided detail synthesis for building mass models using style-synchonized gans. ACM Trans. Graph. 37(6), 1:1\u20131:14 (2018)","DOI":"10.1145\/3272127.3275065"},{"key":"13_CR39","doi-asserted-by":"crossref","unstructured":"Kim, S., Kim, D., Choi, S.: Citycraft: 3d virtual city creation from a single image. Visual Comput. 36 (2020)","DOI":"10.1007\/s00371-019-01701-x"},{"key":"13_CR40","first-page":"p366","volume-title":"A Generative Theory of Shape","author":"M Leyton","year":"2001","unstructured":"Leyton, M.: A Generative Theory of Shape, vol. 2145, p. p366. Springer, Heidelberg (2001)"},{"key":"13_CR41","doi-asserted-by":"crossref","unstructured":"Li, C., Pan, H., Bousseau, A., Mitra, N.J.: Free2cad: parsing freehand drawings into cad commands. ACM TOG (2022)","DOI":"10.1145\/3528223.3530133"},{"key":"13_CR42","doi-asserted-by":"crossref","unstructured":"Li, C., Pan, H., Liu, Y., Tong, X., Sheffer, A., Wang, W.: Robust flow-guided neural prediction for sketch-based freeform surface modeling. ACM Trans. Graph. 37(6) (2018)","DOI":"10.1145\/3272127.3275051"},{"key":"13_CR43","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.isprsjprs.2022.08.027","volume":"193","author":"L Li","year":"2022","unstructured":"Li, L.: Point2roof: end-to-end 3d building roof modeling from airborne lidar point clouds. ISPRS J. Photogramm. Remote Sens. 193, 17\u201328 (2022)","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"13_CR44","doi-asserted-by":"crossref","unstructured":"Li, X., Wen, C., Wang, L., Fang, Y.: Geometry-aware segmentation of remote sensing images via joint height estimation. IEEE Geosci. Remote Sens. Lett. 19 (2021)","DOI":"10.1109\/LGRS.2021.3058168"},{"key":"13_CR45","doi-asserted-by":"crossref","unstructured":"Li, Z., Snavely, N.: Megadepth: learning single-view depth prediction from internet photos. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, UT, USA, 18\u201322 June 2018, pp. 2041\u20132050. Computer Vision Foundation\/IEEE Computer Society (2018)","DOI":"10.1109\/CVPR.2018.00218"},{"key":"13_CR46","doi-asserted-by":"crossref","unstructured":"Lin, C.H., et al.: Infinicity: infinite-scale city synthesis. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV) (2023)","DOI":"10.1109\/ICCV51070.2023.02085"},{"key":"13_CR47","doi-asserted-by":"crossref","unstructured":"Lipson, L., Teed, Z., Deng, J.: Raft-stereo: multilevel recurrent field transforms for stereo matching. In: 2021 International Conference on 3D Vision (3DV), pp. 218\u2013227. IEEE (2021)","DOI":"10.1109\/3DV53792.2021.00032"},{"key":"13_CR48","doi-asserted-by":"crossref","unstructured":"Liu, Z., Zhang, F., Cheng, Z.: Buildingsketch: freehand mid-air sketching for building modeling. In: IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE (2021)","DOI":"10.1109\/ISMAR52148.2021.00049"},{"key":"13_CR49","doi-asserted-by":"crossref","unstructured":"Lun, Z., Gadelha, M., Kalogerakis, E., Maji, S., Wang, R.: 3d shape reconstruction from sketches via multi-view convolutional networks. In: International Conference on 3D Vision (3DV) (2017)","DOI":"10.1109\/3DV.2017.00018"},{"key":"13_CR50","doi-asserted-by":"crossref","unstructured":"Luo, L., Chowdhury, P.N., Xiang, T., Song, Y.Z., Gryaditskaya, Y.: 3d vr sketch guided 3d shape prototyping and exploration. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (2023)","DOI":"10.1109\/ICCV51070.2023.00850"},{"key":"13_CR51","unstructured":"Mahdi, E., Ziming, Z., Xinming, H.: Aerial height prediction and refinement neural networks with semantic and geometric guidance. arXiv preprint arXiv:2011.10697 (2020)"},{"key":"13_CR52","doi-asserted-by":"crossref","unstructured":"Mahmud, J., Price, T., Bapat, A., Frahm, J.M.: Boundary-aware 3d building reconstruction from a single overhead image. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.00052"},{"key":"13_CR53","doi-asserted-by":"crossref","unstructured":"Mescheder, L.M., Oechsle, M., Niemeyer, M., Nowozin, S., Geiger, A.: Occupancy networks: learning 3d reconstruction in function space. In: IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2019, Long Beach, CA, USA, 16\u201320 June 2019, pp. 4460\u20134470. Computer Vision Foundation\/IEEE, Long Beach (2019)","DOI":"10.1109\/CVPR.2019.00459"},{"key":"13_CR54","unstructured":"Mou, L., Zhu, X.X.: Im2height: height estimation from single monocular imagery via fully residual convolutional-deconvolutional network. arXiv preprint arXiv:1802.10249 (2018)"},{"key":"13_CR55","unstructured":"Nam, G., Khlifi, M., Rodriguez, A., Tono, A., Zhou, L., Guerrero, P.: 3d-ldm: neural implicit 3d shape generation with latent diffusion models. arXiv preprint arXiv:2212.00842 (2022)"},{"key":"13_CR56","doi-asserted-by":"crossref","unstructured":"Nishida, G., Garcia-Dorado, I., Aliaga, D.G., Benes, B., Bousseau, A.: Interactive sketching of urban procedural models. ACM Trans. Graph. (TOG) 35(4) (2016)","DOI":"10.1145\/2897824.2925951"},{"key":"13_CR57","doi-asserted-by":"crossref","unstructured":"Park, J.J., Florence, P., Straub, J., Newcombe, R., Lovegrove, S.: Deepsdf: learning continuous signed distance functions for shape representation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.00025"},{"key":"13_CR58","unstructured":"Pearl, O., Lang, I., Hu, Y., Yeh, R.A., Hanocka, R.: Geocode: interpretable shape programs. arXiv preprint arXiv:2212.11715 (2022)"},{"key":"13_CR59","doi-asserted-by":"crossref","unstructured":"Pitts, G., Luther, M.: A parametric approach to 3d massing and density modelling. In: Digital Physicality: Proceedings of the 30th eCAADe Conference, pp. 157\u2013165 (2012)","DOI":"10.52842\/conf.ecaade.2012.1.157"},{"key":"13_CR60","doi-asserted-by":"crossref","unstructured":"Puhachov, I., Martens, C., Kry, P.G., Bessmeltsev, M.: Reconstruction of machine-made shapes from bitmap sketches. ACM Trans. Graph. 42(6) (2023)","DOI":"10.1145\/3618361"},{"issue":"3","key":"13_CR61","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1109\/TPAMI.2020.3019967","volume":"44","author":"R Ranftl","year":"2020","unstructured":"Ranftl, R., Lasinger, K., Hafner, D., Schindler, K., Koltun, V.: Towards robust monocular depth estimation: mixing datasets for zero-shot cross-dataset transfer. IEEE Trans. Pattern Anal. Mach. Intell. 44(3), 1623\u20131637 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR62","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, 18\u201324 June 2022, pp. 10674\u201310685. IEEE, New Orleans (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"13_CR63","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"issue":"4","key":"13_CR64","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1145\/321356.321357","volume":"13","author":"A Rosenfeld","year":"1966","unstructured":"Rosenfeld, A., Pfaltz, J.L.: Sequential operations in digital picture processing. J. ACM (JACM) 13(4), 471\u2013494 (1966)","journal-title":"J. ACM (JACM)"},{"key":"13_CR65","unstructured":"Saxena, S., Kar, A., Norouzi, M., Fleet, D.J.: Monocular depth estimation using diffusion models. CoRR arxiv:2302.14816 (2023)"},{"key":"13_CR66","doi-asserted-by":"publisher","unstructured":"Sayed, M., Gibson, J., Watson, J., Prisacariu, V., Firman, M., Godard, C.: Simplerecon: 3d reconstruction without 3d convolutions. In: ECCV 2022, vol. 13693, pp. 1\u201319. Springer, Heidelberg (2022). https:\/\/doi.org\/10.1007\/978-3-031-19827-4_1","DOI":"10.1007\/978-3-031-19827-4_1"},{"key":"13_CR67","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1007\/978-3-319-46487-9_31","volume-title":"Computer Vision \u2013 ECCV 2016","author":"JL Sch\u00f6nberger","year":"2016","unstructured":"Sch\u00f6nberger, J.L., Zheng, E., Frahm, J.-M., Pollefeys, M.: Pixelwise view selection for unstructured multi-view stereo. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9907, pp. 501\u2013518. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46487-9_31"},{"key":"13_CR68","unstructured":"Shneiderman, B.: Human-Centered AI. Oxford University Press, Oxford (2022). https:\/\/books.google.co.uk\/books?id=YS9VEAAAQBAJ"},{"key":"13_CR69","doi-asserted-by":"crossref","unstructured":"Stucker, C., Schindler, K.: Resdepth: a deep residual prior for 3d reconstruction from high-resolution satellite images. ISPRS J. Photogram. Remote Sens. 183 (2022)","DOI":"10.1016\/j.isprsjprs.2021.11.009"},{"key":"13_CR70","doi-asserted-by":"crossref","unstructured":"Su, W., Du, D., Yang, X., Zhou, S., Fu, H.: Interactive sketch-based normal map generation with deep neural networks. In: Proceedings of the ACM on Computer Graphics and Interactive Techniques, vol. 1, no. 1 (2018)","DOI":"10.1145\/3203186"},{"key":"13_CR71","unstructured":"Tan, M., Le, Q.: Efficientnet: rethinking model scaling for convolutional neural networks. In: International Conference on Machine Learning. PMLR (2019)"},{"key":"13_CR72","unstructured":"Tono, A., Huang, H., Agrawal, A., Fischer, M.: Vitruvio: 3d building meshes via single perspective sketches. arXiv preprint arXiv:2210.13634 (2022)"},{"key":"13_CR73","doi-asserted-by":"publisher","unstructured":"Wang, J., Lin, J., Yu, Q., Liu, R., Chen, Y., Yu, S.X.: 3d shape reconstruction from free-hand sketches. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds.) ECCV Workshops 2022, pp. 184\u2013202. Springer, Heidelberg (2022). https:\/\/doi.org\/10.1007\/978-3-031-25085-9_11","DOI":"10.1007\/978-3-031-25085-9_11"},{"key":"13_CR74","doi-asserted-by":"crossref","unstructured":"Wang, Y., Zorzi, S., Bittner, K.: Machine-learned 3d building vectorization from satellite imagery. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops. CVPR Workshops 2021, virtual, 19\u201325 June 2021, pp. 1072\u20131081. Computer Vision Foundation\/IEEE, Virtual (2021)","DOI":"10.1109\/CVPRW53098.2021.00118"},{"key":"13_CR75","doi-asserted-by":"crossref","unstructured":"Watson, J., Vicente, S., Aodha, O.M., Godard, C., Brostow, G.J., Firman, M.: Heightfields for efficient scene reconstruction for AR. In: IEEE\/CVF Winter Conference on Applications of Computer Vision, WACV 2023, Waikoloa, HI, USA, 2\u20137 January 2023, pp. 5839\u20135849. IEEE (2023)","DOI":"10.1109\/WACV56688.2023.00580"},{"key":"13_CR76","doi-asserted-by":"crossref","unstructured":"Wu, J., Zhang, C., Zhang, X., Zhang, Z., Freeman, W.T., Tenenbaum, J.B.: Learning shape priors for single-view 3d completion and reconstruction. In: ECCV (2018)","DOI":"10.1007\/978-3-030-01252-6_40"},{"key":"13_CR77","doi-asserted-by":"crossref","unstructured":"Xie, H., Chen, Z., Hong, F., Liu, Z.: Citydreamer: compositional generative model of unbounded 3d cities. arXiv preprint arXiv:2309.00610 (2023)","DOI":"10.1109\/CVPR52733.2024.00923"},{"key":"13_CR78","doi-asserted-by":"crossref","unstructured":"Yao, Y., Luo, Z., Li, S., Fang, T., Quan, L.: MVSNet: depth inference for unstructured multi-view stereo. In: ECCV (2018)","DOI":"10.1007\/978-3-030-01237-3_47"},{"key":"13_CR79","doi-asserted-by":"crossref","unstructured":"Yao, Y., Schertler, N., Rosales, E., Rhodin, H., Sigal, L., Sheffer, A.: Front2back: single view 3d shape reconstruction via front to back prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.00061"},{"key":"13_CR80","doi-asserted-by":"crossref","unstructured":"Yin, W., Liu, Y., Shen, C., Yan, Y.: Enforcing geometric constraints of virtual normal for depth prediction. In: 2019 IEEE\/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), 27 October\u20132 November 2019, pp. 5683\u20135692. IEEE (2019)","DOI":"10.1109\/ICCV.2019.00578"},{"key":"13_CR81","doi-asserted-by":"crossref","unstructured":"Yin, W., et al.: Learning to recover 3d scene shape from a single image. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 204\u2013213 (2021)","DOI":"10.1109\/CVPR46437.2021.00027"},{"key":"13_CR82","first-page":"1","volume":"17","author":"J \u017dbontar","year":"2016","unstructured":"\u017dbontar, J., LeCun, Y.: Stereo matching by training a convolutional neural network to compare image patches. JMLR 17, 1\u201332 (2016)","journal-title":"JMLR"},{"key":"13_CR83","doi-asserted-by":"crossref","unstructured":"Zhang, S.H., Guo, Y.C., Gu, Q.W.: Sketch2model: view-aware 3d modeling from single free-hand sketches. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6012\u20136021 (2021)","DOI":"10.1109\/CVPR46437.2021.00595"},{"key":"13_CR84","doi-asserted-by":"crossref","unstructured":"Zhao, C., Sun, Q., Zhang, C., Tang, Y., Qian, F.: Monocular depth estimation based on deep learning: an overview. Sci. China Technol. Sci. 63(9) (2020)","DOI":"10.1007\/s11431-020-1582-8"},{"key":"13_CR85","doi-asserted-by":"crossref","unstructured":"Zhao, L., Wang, H., Zhu, Y., Song, M.: A review of 3d reconstruction from high-resolution urban satellite images. Int. J. Remote Sens. 44(2) (2023)","DOI":"10.1080\/01431161.2023.2169844"},{"key":"13_CR86","unstructured":"Zheng, J., Zhu, Y., Wang, K., Zou, Q., Zhou, Z.: Deep learning assisted optimization for 3d reconstruction from single 2d line drawings. arXiv e-prints pp. arXiv\u20132209 (2022)"},{"key":"13_CR87","doi-asserted-by":"crossref","unstructured":"Zheng, X.Y., Pan, H., Wang, P.S., Tong, X., Liu, Y., Shum, H.Y.: Locally attentional sdf diffusion for controllable 3d shape generation. ACM Trans. Graph. 42(4) (2023)","DOI":"10.1145\/3592103"},{"key":"13_CR88","doi-asserted-by":"crossref","unstructured":"Zhong, Y., Gryaditskaya, Y., Zhang, H., Song, Y.: Deep sketch-based modeling: tips and tricks. In: Struc, V., Fern\u00e1ndez, F.G. (eds.) International Conference on 3D Vision (3DV). IEEE (2020)","DOI":"10.1109\/3DV50981.2020.00064"},{"key":"13_CR89","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.cag.2022.06.005","volume":"106","author":"Y Zhong","year":"2022","unstructured":"Zhong, Y., Gryaditskaya, Y., Zhang, H., Song, Y.Z.: A study of deep single sketch-based modeling: view\/style invariance, sparsity and latent space disentanglement. Comput. Graph. 106, 237\u2013247 (2022)","journal-title":"Comput. Graph."},{"key":"13_CR90","doi-asserted-by":"crossref","first-page":"3518","DOI":"10.1109\/TCSVT.2020.3040900","volume":"31","author":"Y Zhong","year":"2020","unstructured":"Zhong, Y., Qi, Y., Gryaditskaya, Y., Zhang, H., Song, Y.Z.: Towards practical sketch-based 3d shape generation: the role of professional sketches. IEEE Trans. Circuits Syst. Video Technol. 31, 3518\u20133528 (2020)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"13_CR91","unstructured":"Zhou, B., Russakovsky, O., Fong, R., Hoffman, J.: CVPR tutorial on human-centered AI for computer vision (2022). https:\/\/human-centeredai.github.io\/"},{"key":"13_CR92","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-00889-5_1","volume-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support","author":"Z Zhou","year":"2018","unstructured":"Zhou, Z., Rahman Siddiquee, M.M., Tajbakhsh, N., Liang, J.: UNet++: a nested U-net architecture for medical image segmentation. In: Stoyanov, D., et al. (eds.) DLMIA\/ML-CDS -2018. LNCS, vol. 11045, pp. 3\u201311. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00889-5_1"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73209-6_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,8]],"date-time":"2025-04-08T12:22:05Z","timestamp":1744114925000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73209-6_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,1]]},"ISBN":["9783031732089","9783031732096"],"references-count":92,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73209-6_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,1]]},"assertion":[{"value":"1 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}