F. Paris and . .. Nantes, , p.148

. .. Classifier,

. .. Advanced-features-contributions, 3.3 Graph kernels and ScatNet to baseline comparison, p.169

. Third,

, Elancourt FUS Facet Under Segmentation. xv, xvi, vol.78, p.81

G. , Group equivariant Convolutional Neural Network, vol.128

, GIS Geographic Information Science, vol.36, p.61

, IFC Industry Foundation Classes. xv, p.46

, IGN Institut National de l'Information Géographique et Forestière. i, p.39

, ISPRS International Society for Photogrammetry and Remote Sensing, p.51

, LCC Linear Cell Complex, vol.50

, LiDAR Light Detection And Ranging. xv, vol.36, p.88

, LoD Level of Detail. xv, xvi, vol.46, p.107

, MKL Multiple Kernel Learning, vol.139, p.190

, NDVI Normalized Difference Vegetation Index, p.65

, OGC Open Geospatial Consortium, vol.50

, RaDAR Radio Detection And Ranging, p.47

, RBF Radial Basis Function, vol.139, p.190

. Rf-random-forest, , vol.88, p.235

. Scatnet-scattering-network, , vol.56, pp.212-217

, SfM Structure-from-Motion, vol.88

, SMO Sequential Minimal Optimization, vol.188, p.190

. Svm-support-vector-machine, , vol.88, p.235

, VHR Very High Resolution, vol.56, p.99

. Bibliography-adeline, R. M. Karine, M. Chen, X. Briottet, S. K. Pang et al., Shadow detection in very high spatial resolution aerial images: A comparative study, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.80, p.60, 2013.

F. Aiolli and M. Donini, EasyMKL: a scalable multiple kernel learning algorithm, Neurocomputing, vol.169, p.145, 2015.

D. Akca, M. Freeman, I. Sargent, and A. Gruen, Quality assessment of 3D building data, vol.132, p.65, 2010.

N. Alam, D. Wagner, M. Wewetzer, J. Von-falkenhausen, and V. Coors, Towards automatic validation and healing of CityGML models for geometric and semantic consistency, Innovations in 3D Geo-Information Sciences, p.50, 2014.

F. Albrecht, I. Moser, and . Hijazi, Assessing façade visibility in 3D city models for city marketing, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, p.39, 2013.

J. Andèn and S. Mallat, Deep scattering spectrum, IEEE Transactions on Signal Processing, vol.62, p.140, 2014.

M. Andreux, T. Angles, G. Exarchakis, R. Leonarduzzi, and G. Rochette, Kymatio: Scattering Transforms in Python, p.145, 2018.

S. Ardeshir, A. Amir-roshan-zamir, M. Torroella, and . Shah, GIS-assisted object detection and geospatial localization, European Conference on Computer Vision (ECCV), p.38, 2014.

A. Armagan, M. Hirzer, and V. Lepetit, Semantic segmentation for 3D localization in urban environments, Joint Urban Remote Sensing Event (JURSE). IEEE, p.42, 2017.

N. Aronszajn, Theory of reproducing kernels, In: Transactions of the American mathematical society, vol.68, p.189, 1950.

A. Ohori, H. Ken, J. Ledoux, and . Stoter, A dimension-independent extrusion algorithm using generalised maps, In: International Journal of Geographical Information Science, vol.29, p.61, 2015.

C. Arth, C. Pirchheim, J. Ventura, D. Schmalstieg, and V. Lepetit, Instant outdoor localization and slam initialization from 2.5 d maps, IEEE Transactions on Visualization and Computer Graphics, vol.21, p.38, 2015.

. Aubry, . Mathieu, C. Bryan, J. Russell, and . Sivic, Painting-to-3D model alignment via discriminative visual elements, In: ACM Transactions on Graphics (ToG), vol.33, p.39, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00863615

C. Baillard, C. Schmid, A. Zisserman, and A. Fitzgibbon, Automatic line matching and 3D reconstruction of buildings from multiple views, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 3-2W5, vol.72, p.61, 1999.
URL : https://hal.archives-ouvertes.fr/inria-00590111

F. Bao, D. Yan, J. Niloy, P. Mitra, and . Wonka, Generating and exploring good building layouts, In: ACM Transactions on Graphics (ToG), vol.32, p.62, 2013.

M. Berger, A. Tagliasacchi, L. Seversky, P. Alliez, and J. Levine, State of the Art in Surface Reconstruction from Point Clouds, Eurographics 2014 -State of the Art Reports, vol.1, p.51, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01017700

F. Biljecki and Y. Dehbi, Raise the roof: towards generating LoD2 models without aerial surveys using machine learning, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV.4/W8, p.60, 2019.

F. Biljecki, G. Heuvelink, H. Ledoux, and J. Stoter, Propagation of positional error in 3D GIS: estimation of the solar irradiation of building roofs, In: International Journal of Geographical Information Science, vol.29, p.26, 2015.

F. Biljecki, H. Ledoux, X. Du, J. Stoter, and K. Huat-soon, The most common geometric and semantic errors in citygml datasets, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.4, p.27, 2016.

F. Biljecki, H. Ledoux, and J. Stoter, An improved LOD specification for 3D building models, In: Computers, Environment and Urban Systems, vol.59, pp.25-37, 2016.

F. Biljecki, H. Ledoux, and J. Stoter, Generating 3D city models without elevation data, Computers, Environment and Urban Systems, vol.64, p.60, 2017.

F. Biljecki, H. Ledoux, J. Stoter, and J. Zhao, Formalisation of the level of detail in 3D city modelling, In: Computers, Environment and Urban Systems, vol.48, p.46, 2014.

F. Biljecki, J. Stoter, H. Ledoux, S. Zlatanova, and A. Çöltekin, Applications of 3D City Models: State of the Art Review, ISPRS International Journal of Geo, vol.44, pp.2842-2889, 2015.

R. Billen and S. Zlatanova, 3D spatial relationships model: a useful concept for 3D cadastre?, In: Computers, Environment and Urban Systems, vol.27, p.36, 2003.

. Bonin-font, A. Francisco, G. Ortiz, and . Oliver, Visual navigation for mobile robots: A survey, In: Journal of intelligent and robotic systems, vol.53, p.38, 2008.

A. Bordes, S. Ertekin, J. Weston, and L. Bottou, Fast kernel classifiers with online and active learning, In: Journal of Machine Learning Research, vol.6, p.190, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00752361

K. M. Borgwardt and H. Kriegel, Shortest-path kernels on graphs, Fifth IEEE International Conference on Data Mining. ICDM '05. IEEE, vol.139, p.137, 2005.

B. E. Boser, V. N. Isabelle-m-guyon, and . Vapnik, A training algorithm for optimal margin classifiers, fifth annual workshop on Computational learning theory, p.189, 1992.

L. Boudet, N. Paparoditis, F. Jung, G. Martinoty, and M. Pierrot-deseilligny, A supervised classification approach towards quality self-diagnosis of 3D building models using digital aerial imagery, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVI.3, vol.82, pp.136-141, 2006.

E. Brachmann and C. Rother, Learning less is more-6d camera localization via 3d surface regression, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, p.47, 2018.

M. Brasebin, J. Perret, M. Borne, P. Chapron, and I. Lokhat, SimPLU3D, p.38, 2014.

M. Brasebin, J. Perret, S. Mustière, and C. Weber, 3D urban data to assess local urban regulation influence, In: Computers, Environment and Urban Systems, vol.68, p.36, 2018.

M. Brasebin, J. Perret, and R. Reuillon, Stochastic buildings generation to assist in the design of right to build plans, Advances in 3D Geoinformation, p.38, 2017.

C. Brechbühler, G. Gerig, and O. Kübler, Parametrization of closed surfaces for 3-D shape description, Computer Vision and Image Understanding 61, vol.2, p.63, 1995.

M. Brédif, D. Boldo, M. Pierrot-deseilligny, and H. Maître, 3D building reconstruction with parametric roof superstructures, IEEE International Conference on Image Processing, pp.537-540, 2007.

M. Brédif, 3D Building Modeling: Topology-Aware Kinetic Fitting of Polyhedral Roofs and Automatic Roof Superstructure Reconstruction, p.102, 2010.

L. Breiman, R. Friedman, C. J. Olshen, and . Stone, Classification and Regression Trees, 1984.

L. Breiman, Bagging predictors, Machine learning 24, vol.2, p.195, 1996.

L. Breiman, Random forests, Machine Learning 45.1, p.195, 2001.

J. Bruna and S. Mallat, Invariant scattering convolution networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, pp.1872-1886, 2013.

A. Budroni and J. Böhm, Automatic 3D modelling of indoor manhattanworld scenes from laser data, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, p.40, 2010.

G. Castellazzi, G. Antonio-d'altri, I. Bitelli, A. Selvaggi, and . Lambertini, From laser scanning to finite element analysis of complex buildings by using a semi-automatic procedure, p.48, 2015.

F. Cazals and J. Giesen, In: Effective Computational Geometry for Curves and Surfaces, p.51, 2006.

T. Cham, A. Ciptadi, W. Tan, M. Pham, and L. Chia, Estimating camera pose from a single urban ground-view omnidirectional image and a 2D building outline map, Conference on Computer Vision and Pattern Recognition, p.38, 2010.

A. Chauve, P. Labatut, and J. Pons, Robust piecewise-planar 3D reconstruction and completion from large-scale unstructured point data, IEEE Conference on Computer Vision and Pattern Recognition, p.61, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00654408

. Chen, C. Liang-chien, T. Wu, C. Shen, and . Chou, The application of geometric network models and building information models in geospatial environments for fire-fighting simulations, In: Computers, Environment and Urban Systems, vol.45, p.39, 2014.

Y. Chen, A. Ebenstein, M. Greenstone, and H. Li, Evidence on the impact of sustained exposure to air pollution on life expectancy from China's Huai River policy, In: National Academy of Sciences, vol.110, p.37, 2013.

G. Christie, G. Warnell, and K. Kochersberger, Semantics for UGV Registration in GPS-denied Environments, p.38, 2016.

T. Cohen and M. Welling, Group equivariant convolutional networks, International conference on machine learning, pp.2990-2999, 2016.

M. Colomb, M. Brasebin, J. Perret, and C. Tannier, Simulation of a realistic residential development with the integration of two existing models, European Colloquium on Theoretical and Quantitative Geography, p.36, 2017.
URL : https://hal.archives-ouvertes.fr/hal-02554027

C. Cortes and V. Vapnik, Support-vector networks, Machine learning 20.3, p.187, 1995.

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, International Conference on Computer Vision & Pattern Recognition (CVPR '05). Ed. by Cordelia Schmid, Stefano Soatto, and Carlo Tomasi, vol.1, p.91, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548512

G. Damiand and P. Lienhardt, Combinatorial maps: efficient data structures for computer graphics and image processing, p.50, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01090890

. Demir, D. G. Ilke, B. Aliaga, and . Benes, Procedural editing of 3d building point clouds, IEEE International Conference on Computer Vision (ICCV), pp.2147-2155, 2015.

Y. Deng, C. P. Jack, C. Cheng, and . Anumba, Mapping between BIM and 3D GIS in different levels of detail using schema mediation and instance comparison, In: Automation in Construction, vol.67, p.45, 2016.

A. Devaux, C. Hoarau, M. Brédif, S. Christophe, and ;. Urban-geovisu-alization, SITU AUGMENTED AND MIXED REALITY EXPERIMENTS." In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01882336

A. Devaux, M. Brédif, and N. Paparoditis, A web-based 3d mapping application using webgl allowing interaction with images, point clouds and models, International Conference on Advances in Geographic Information Systems, p.43, 2012.
URL : https://hal.archives-ouvertes.fr/hal-02551502

A. Diakité, G. Abou, D. Damiand, and . Van-maercke, Topological reconstruction of complex 3D buildings and automatic extraction of levels of detail, Eurographics Workshop on Urban Data Modelling and Visualisation. Eurographics Association, p.50, 2014.

A. R. Dick, H. S. Philip, R. Torr, and . Cipolla, Modelling and interpretation of architecture from several images, In: International Journal of Computer Vision, vol.60, issue.2, p.65, 2004.

K. Dimitropoulos, N. Köse, E. Grammalidis, and . Cetin, Fire detection and 3D fire propagation estimation for the protection of cultural heritage areas, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.38, p.37, 2010.

L. Duan and F. Lafarge, Towards large-scale city reconstruction from satellites, European Conference on Computer Vision (ECCV), p.63, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01352466

M. Durupt and F. Taillandier, Automatic building reconstruction from a Digital Elevation Model and cadastral data: an operational approach, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVI.3, vol.102, p.99, 2006.

M. Eickenberg, G. Exarchakis, M. Hirn, S. Mallat, and L. Thiry, Solid harmonic wavelet scattering for predictions of molecule properties, In: The Journal of chemical physics, vol.148, p.140, 2018.

S. Elberink, G. Oude, and . Vosselman, Quality analysis on 3D building models reconstructed from airborne laser scanning data, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.66, pp.157-165, 2011.

O. Ennafii and A. Le-bris, Semantic evaluation of 3D city models, Florent Lafarge, and Clément Mallet, p.80, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01875781

O. Ennafii, A. Le-bris, F. Lafarge, and C. Mallet, Qualification sémantique de modèles 3D de bâtiments, Conférence Française de Photogrammétrie et de Télédétection (CFPT) (cit, p.95, 2018.

A. Fabri, G. Giezeman, L. Kettner, S. Schirra, and S. Schönherr, On the design of CGAL a computational geometry algorithms library, vol.11, p.31, 2000.

A. Feragen, N. Kasenburg, J. Petersen, M. De-bruijne, and K. Borgwardt, Scalable kernels for graphs with continuous attributes, Advances in Neural Information Processing Systems (NIPS), pp.216-224, 2013.

R. A. Fisher, The use of multiple measurements in taxonomic problems, In: Annals of eugenics, issue.2, p.191, 1936.

T. Gärtner, P. Flach, and S. Wrobel, On graph kernels: Hardness results and efficient alternatives, Learning theory and kernel machines, p.133, 2003.

S. Ghosh, N. Das, T. Gonçalves, P. Quaresma, and M. Kundu, The journey of graph kernels through two decades, Computer Science Review, vol.27, p.130, 2018.

B. Gilbert, I'm blown away by the virtual New York City of 'Spider-Man' on PlayStation 4 -here's how it compares to the real thing, p.38, 2018.

B. Gorszczyk, G. Damiand, S. Servigne, A. Abou-diakite, and G. Gesquière, An Automatic Comparison Approach to Detect Errors on 3D City Models, Eurographics Workshop on Urban Data Modelling and Visualisation. Ed. by The Eurographics Association. Proceedings. Liège, Belgium, p.50, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01458396

G. Gröger, T. H. Kolbe, and C. Nagel, OGC City Geography Markup Language (CityGML) Encoding Standard, p.50, 2012.

G. Gröger and L. Plümer, CityGML-Interoperable semantic 3D city models, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.71, p.27, 2012.

G. Gröger and L. Plümer, How to achieve consistency for 3D city models, p.50, 2011.

A. Gupta, J. Johnson, L. Fei-fei, S. Savarese, and A. Alahi, Social gan: Socially acceptable trajectories with generative adversarial networks, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, p.38, 2018.

I. Guyon, J. Weston, S. Barnhill, and V. Vapnik, Gene Selection for Cancer Classification using Support Vector Machines, In: Machine Learning, vol.46, issue.1, p.154, 2002.

R. Hammack, W. Imrich, and S. Klav?ar, Handbook of product graphs, p.132, 2011.

M. Harrach, A. Devaux, and M. Brédif, Interactive image geolocalization in an immersive web application, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII.2/W9, p.43, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02526285

D. Haussler, Convolution kernels on discrete structures, p.137, 1999.

O. Henricsson and E. Baltsavias, 3-D Building reconstruction with ARUBA: a qualitative and quantitative evaluation, vol.65, p.63, 1997.

M. Hofer, M. Maurer, and H. Bischof, Efficient 3D scene abstraction using line segments, Computer Vision and Image Understanding, vol.157, p.75, 2017.

T. Holzmann, M. Maurer, F. Fraundorfer, and H. Bischof, Semantically Aware Urban 3D Reconstruction with Plane-Based Regularization, European Conference on Computer Vision (ECCV) (cit, p.61, 2018.

S. Horna, G. Damiand, D. Meneveaux, and Y. Bertrand, Building 3D indoor scenes topology from 2D architectural plans, GRAPP. Proc. of 2nd International Conference on Computer Graphics Theory and Applications, p.60, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00337793

T. Horváth, T. Gärtner, and S. Wrobel, Cyclic pattern kernels for predictive graph mining, tenth ACM SIGKDD international conference on Knowledge discovery and data mining, p.133, 2004.

A. Huck and J. Monstadt, Urban and infrastructure resilience: Diverging concepts and the need for cross-boundary learning, In: Environmental Science & Policy, vol.100, p.37, 2019.

C. Iovan, D. Boldo, and M. Cord, Detection, characterization, and modeling vegetation in urban areas from high-resolution aerial imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.1, issue.3, p.42, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01170701

O. Jamet, O. Dissard, and S. Airault, Building extraction from stereo pairs of aerial images: accuracy and productivity constraint of a topographic production line, p.48, 1995.

C. Jaynes, E. Riseman, and A. Hanson, Recognition and reconstruction of buildings from multiple aerial images, Computer Vision and Image Understanding 90.1, vol.65, pp.68-98, 2003.

. Jethava, A. Vinay, C. Martinsson, D. Bhattacharyya, and . Dubhashi, Lovász ? function, SVMs and finding dense subgraphs, In: The Journal of Machine Learning Research, vol.14, issue.1, p.134, 2013.

F. Johansson, V. Jethava, D. Dubhashi, and C. Bhattacharyya, Global graph kernels using geometric embeddings, 31st International Conference on Machine Learning, p.134, 2014.

H. Kaartinen, . Hyyppä, G. Gülch, H. Vosselman, and . Hyyppä, In: International archives of photogrammetry, remote sensing and spatial information sciences XXXVI.3/W19, vol.65, pp.227-232, 2005.

M. Kedzierski and A. Fryskowska, Terrestrial and aerial laser scanning data integration using wavelet analysis for the purpose of 3D building modeling, p.47, 2014.

Y. Kim, S. Min, I. Ryu, and . Kim, Planar Abstraction and Inverse Rendering of 3D Indoor Environment, IEEE Transactions on Visualization and Computer Graphics, p.39, 2019.

T. H. Kolbe, G. Gröger, and L. Plümer, CityGML: Interoperable access to 3D city models, pp.883-899, 2005.

R. Kondor and H. Pan, The multiscale laplacian graph kernel, Advances in Neural Information Processing Systems (NIPS), pp.2990-2998, 2016.

A. Koutsoudis, F. Arnaoutoglou, and C. Chamzas, On 3D reconstruction of the old city of Xanthi. A minimum budget approach to virtual touring based on photogrammetry, In: Journal of Cultural Heritage, vol.8, issue.1, p.39, 2007.

P. Koutsourakis, L. Simon, and O. Teboul, Single view reconstruction using shape grammars for urban environments, IEEE International Conference on Computer Vision (ICCV). IEEE, p.61, 2009.

A. Kovashka, O. Russakovsky, L. Fei-fei, and K. Grauman, Crowdsourcing in computer vision, Foundations and Trends® in Computer Graphics and Vision, vol.10, p.54, 2016.

A. Kowdle, Y. Chang, A. Gallagher, and T. Chen, Active learning for piecewise planar 3D reconstruction, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, vol.88, pp.929-936, 2011.

N. M. Kriege, D. Fredrik, C. Johansson, and . Morris, A survey on graph kernels, In: Applied Network Science, vol.5, issue.1, p.130, 2020.

V. Kurakula, H. Skidmore, . Kluijver, . Stoter, and . Dabrowska-zielinska, The Netherlands: International Institute for Geo-information Science and Earth Observation (cit, p.40, 2007.

M. Kwan and J. Lee, Emergency response after 9/11: the potential of real-time 3D GIS for quick emergency response in micro-spatial environments, Computers, Environment and Urban Systems, vol.29, p.39, 2005.

F. Lafarge, Some new research directions to explore in urban reconstruction, Joint Urban Remote Sensing Event (JURSE). IEEE, pp.1-4, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01112503

F. Lafarge, X. Descombes, J. Zerubia, and M. Pierrot-deseilligny, Structural approach for building reconstruction from a single DSM, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.1, p.61, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00503136

F. Lafarge and C. Mallet, Creating large-scale city models from 3D-point clouds: a robust approach with hybrid representation, In: International Journal of Computer Vision, vol.99, p.70, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00759265

G. R. Lanckriet, T. De-bie, N. Cristianini, W. S. Michael-i-jordan, and . Noble, A statistical framework for genomic data fusion, Bioinformatics 20, vol.16, p.190, 2004.

T. Landes, H. Boulaassal, and P. Grussenmeyer, Quality assessment of geometric façade models reconstructed from TLS data, The Photogrammetric Record, vol.27, pp.137-154, 2012.

P. Langlois, A. Boulch, and R. Marlet, Surface Reconstruction from 3D Line Segments, International Conference on 3D Vision (3DV) (cit, p.75, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02344362

H. Ledoux, On the validation of solids represented with the international standards for geographic information, In: Computer-Aided Civil and Infrastructure Engineering, vol.28, p.27, 2013.

H. Ledoux, val3dity: validation of 3D GIS primitives according to the international standards, Open Geospatial Data, Software and Standards 3.1, vol.69, p.50, 2018.

H. Ledoux and M. Meijers, Topologically consistent 3D city models obtained by extrusion, In: International Journal of Geographical Information Science, vol.25, pp.557-574, 2011.

H. Lee, R. Grosse, R. Ranganath, and A. Ng, Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations, 26th annual international conference on machine learning, p.127, 2009.

M. Li, P. Wonka, and L. Nan, Manhattan-world urban reconstruction from point clouds, European Conference on Computer Vision (ECCV), 2016.

. Springer, , vol.78, p.61

G. G. Løvås, Modeling and simulation of pedestrian traffic flow, In: Transportation Research Part B: Methodological, vol.28, p.41, 1994.

L. Lovász, On the Shannon capacity of a graph, IEEE Transactions on Information theory, vol.25, p.134, 1979.

D. G. Lowe, Distinctive image features from scale-invariant keypoints, In: International Journal of Computer Vision, vol.60, issue.2, p.91, 2004.

D. Ludlow, Urban sprawl in Europe: The ignored challenge, p.36, 2006.

P. Mahé, N. Ueda, T. Akutsu, J. Perret, and J. Vert, In: twenty-first international conference on Machine learning, p.133, 2004.

S. Mallat, Group invariant scattering, In: Communications on Pure and Applied Mathematics, vol.65, pp.1331-1398, 2012.

A. Martinovic and L. Van-gool, Bayesian grammar learning for inverse procedural modeling, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, p.61, 2013.

M. Mathias, A. Martinovic, J. Weissenberg, and L. Van-gool, Procedural 3D building reconstruction using shape grammars and detectors, International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, p.61, 2011.

S. Mayunga, Y. Zhang, and D. Coleman, Semi-automatic building extraction utilizing Quickbird imagery, p.48, 2005.

M. Mcwhertor, Under the hood of Infamous: Second Son's hyper-real Seattle, p.38, 2013.

M. Mezian, B. Vallet, B. Soheilian, and N. Paparoditis, Uncertainty propagation for terrestrial mobile laser scanner, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.41, p.47, 2016.
URL : https://hal.archives-ouvertes.fr/hal-02552550

J. Michelin, J. Tierny, F. Tupin, C. Mallet, and N. Paparoditis, Quality evaluation of 3D city building models with automatic error diagnosis, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL.7/W2, pp.161-166, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01206871

J. Michelin, C. Mallet, and N. David, Building edge detection using small-footprint airborne full-waveform lidar data, p.60, 2012.
URL : https://hal.archives-ouvertes.fr/hal-02384563

. Mnih, G. E. Volodymyr, and . Hinton, Learning to detect roads in highresolution aerial images, European Conference on Computer Vision (ECCV), 2010.

. Springer, , p.42

M. Mohamed, Quality assessment of 3D building models in airborne digital photogrammetry, p.63, 2013.
URL : https://hal.archives-ouvertes.fr/tel-01124145

F. Monnier, Amélioration de la localisation 3D de véhicules mobiles à l'aide de cartes ou modèles 3D, p.48, 2014.

F. Monnier, B. Vallet, N. Paparoditis, J. Papelard, and N. David, Registration of terrestrial mobile laser data on 2D or 3D geographic database by use of a non-rigid ICP approach, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences II.5/W2, p.47, 2013.
URL : https://hal.archives-ouvertes.fr/hal-02552493

P. Mooney, P. Corcoran, and A. C. Winstanley, Towards quality metrics for OpenStreetMap, ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS), p.51, 2010.

P. Musialski, P. Wonka, D. G. Aliaga, M. Wimmer, and L. Van-gool, A survey of urban reconstruction, In: Computer graphics forum, vol.32, 2013.

C. Nagel, A. Stadler, and T. H. Kolbe, Conceptual requirements for the automatic reconstruction of building information models from uninterpreted 3D models, Remote Sensing and Spatial Information Sciences. ISPRS, p.46, 2009.

L. Nan, C. Jiang, B. Ghanem, and P. Wonka, Template assembly for detailed urban reconstruction, Computer Graphics Forum, vol.34, 2015.

L. Nan and P. Wonka, Polyfit: Polygonal surface reconstruction from point clouds, IEEE International Conference on Computer Vision (ICCV), pp.2353-2361, 2017.

P. Neis, M. Goetz, and A. Zipf, Towards automatic vandalism detection in OpenStreetMap, ISPRS International Journal of Geo-Information, vol.1, issue.3, p.55, 2012.

M. Neumann, R. Garnett, C. Bauckhage, and K. Kersting, Propagation kernels: efficient graph kernels from propagated information, vol.2, pp.209-245, 2016.

W. Nguatem and H. Mayer, Modeling Urban Scenes From Pointclouds, IEEE Internatinal Conference on Computer Vision (ICCV). IEEE, vol.63, p.60, 2017.

. Oecd and . Stat, Land cover in Functional Urban Areas, p.42, 2020.

K. Omasa, F. Hosoi, and A. Konishi, 3D lidar imaging for detecting and understanding plant responses and canopy structure, In: Journal of Experimental Botany, vol.58, p.41, 2006.

M. Ortner, X. Descombes, and J. Zerubia, Building outline extraction from Digital Elevation Models using marked point processes, In: International Journal of Computer Vision, vol.72, p.91, 2007.

E. Oyallon and S. Mallat, Deep roto-translation scattering for object classification, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp.2865-2873, 2015.

M. Pascal, M. Corso, O. Chanel, C. Declercq, and C. Badaloni, Assessing the public health impacts of urban air pollution in 25 European cities: results of the Aphekom project, Science of the Total Environment, vol.449, p.37, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01500894

. P?tr?ucean, I. Viorica, M. Armeni, J. Nahangi, I. Yeung et al., State of research in automatic as-built modelling, Advanced Engineering Informatics 29, vol.2, p.44, 2015.

F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, and B. Thirion, Scikitlearn: Machine Learning in Python, In: Journal of Machine Learning Research, vol.12, p.95, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00650905

N. Piasco, D. Sidibé, C. Demonceaux, and V. Gouet-brunet, A survey on visual-based localization: On the benefit of heterogeneous data, Pattern Recognition, vol.74, p.38, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01744680

C. Plante, How Spider-Man PS4's New York City compares to the real thing, p.38, 2013.

J. Platt, Sequential minimal optimization: A fast algorithm for training support vector machines, Advances in Kernel Methods: Support Vector Learning, p.188, 1998.

C. Poullis, A Framework for Automatic Modeling from Point Cloud Data, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, p.61, 2013.

C. Poullis and S. You, Automatic reconstruction of cities from remote sensor data, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, p.60, 2009.

D. Powers, Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation, In: International Journal of Machine Learning Technology, vol.2, issue.1, p.96, 2011.

M. Previtali, R. Luigi-barazzetti, B. Brumana, D. Cuca, and . Oreni, Automatic façade modelling using point cloud data for energy-efficient retrofitting, In: Applied Geomatics, vol.6, p.26, 2014.

A. Rakotomamonjy, F. R. Bach, S. Canu, and Y. Grandvalet, SimpleMKL, In: Journal of Machine Learning Research, vol.9, p.190, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00218338

J. Rau, L. Chen, F. Tsai, . Kuo-hsin, W. Hsiao et al., Lod generation for 3d polyhedral building model, Pacific-Rim Symposium on Image and Video Technology, p.46, 2006.

P. Redweik, C. Catita, and M. Brito, Solar energy potential on roofs and facades in an urban landscape, Solar Energy 97, p.41, 2013.

, 1.0.2. Institut national de l'information géographique et forestière (IGN). 73 avenue de Paris, 94165 Saint-Mandé CEDEX (cit, p.44, 2017.

F. Rottensteiner, G. Sohn, M. Gerke, J. D. Wegner, and U. Breitkopf, Results of the ISPRS benchmark on urban object detection and 3D building reconstruction, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.93, pp.256-271, 2014.

F. Rottensteiner, G. Sohn, J. Jung, M. Gerke, and C. Baillard, The ISPRS benchmark on urban object classification and 3D building reconstruction, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences I-3.1, pp.293-298, 2012.

U. Rüppel and K. Schatz, Designing a BIM-based serious game for fire safety evacuation simulations, In: Advanced Engineering Informatics, vol.25, p.39, 2011.

B. C. Russell, J. Sivic, J. Ponce, and H. Dessales, Automatic alignment of paintings and photographs depicting a 3D scene, IEEE International Conference on Computer Vision (ICCV) Workshops (ICCV Workshops, p.39, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01053879

H. Rüther, M. Hagai, E. G. Martine, and . Mtalo, Application of snakes and dynamic programming optimisation technique in modeling of buildings in informal settlement areas, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.56, p.48, 2002.

H. Schuster and U. Weidner, A new approach towards quantitative quality evaluation of 3D building models, ISPRS Commission IV Joint Workshop on Challenges in Geospatial Analysis, vol.65, p.63, 2003.

W. Shao and D. Terzopoulos, Autonomous pedestrians, Graphical Models, vol.69, p.41, 2007.

J. Shawe-taylor and N. Cristianini, Kernel methods for pattern analysis, p.189, 2004.

N. Shervashidze, P. Schweitzer, E. J. Van-leeuwen, K. Mehlhorn, and K. M. Borgwardt, Weisfeiler-lehman graph kernels, In: Journal of Machine Learning Research, vol.12, pp.2539-2561, 2011.

L. Sifre and S. Mallat, Rotation, scaling and deformation invariant scattering for texture discrimination, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp.1233-1240, 2013.

G. Siglidis, G. Nikolentzos, S. Limnios, C. Giatsidis, and K. Skianis, Grakel: A graph kernel library in python, p.144, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02612740

L. Simon, O. Teboul, P. Koutsourakis, and N. Paragios, Random exploration of the procedural space for single-view 3d modeling of buildings, International Journal of Computer Vision, vol.93, p.61, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00856304

S. Sinha, D. Steedly, and R. Szeliski, Piecewise planar stereo for image-based rendering, Twelfth IEEE International Conference on Computer Vision (ICCV, p.74, 2009.

B. Soheilian, N. Paparoditis, and B. Vallet, Detection and 3D reconstruction of traffic signs from multiple view color images, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.77, p.42, 2013.
URL : https://hal.archives-ouvertes.fr/hal-02552610

J. Stoter, H. De-kluijver, and V. Kurakula, 3D noise mapping in urban areas, International Journal of Geographical Information Science, vol.22, p.37, 2008.

J. E. Stoter, H. Arroyo-ohori, and . Ledoux, Geo-BIM data integration: easier said than done?, In: Geospatial World, vol.9, p.45, 2018.

Z. Sun, N. Ampornpunt, M. Varma, and S. Vishwanathan, Multiple kernel learning and the SMO algorithm, Advances in Neural Information Processing Systems (NIPS), p.190, 2010.

F. Taillandier and R. Deriche, Automatic buildings reconstruction from aerial images: a generic Bayesian framework, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXV.3A (cit. on pp. 60 sq, vol.74, 2004.

A. Taneja, L. Ballan, and M. Pollefeys, City-scale change detection in cadastral 3d models using images, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, p.54, 2013.

C. Tannier, J. Foltête, and X. Girardet, Assessing the capacity of different urban forms to preserve the connectivity of ecological habitats, Landscape and Urban Planning 105.1, p.36, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00736650

H. T. Tavani, Ethics and technology: Controversies, questions, and strategies for ethical computing, p.41, 2011.

J. Thornton, Individual privacy rights with respect to services such as Google Street View, In: ACM SIGCAS Computers and Society, vol.40, p.41, 2010.

H. Tran, K. Khoshelham, and A. Kealy, Geometric comparison and quality evaluation of 3D models of indoor environments, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.149, p.62, 2019.

M. Uden and A. Zipf, Open building models: Towards a platform for crowdsourcing virtual 3D cities, Progress and New Trends in 3D Geoinformation Sciences, p.45, 2013.

U. Ujang, F. Anton, and A. Abdul-rahman, Unified Data Model of Urban Air Pollution Dispersion and 3D Spatial City Models: Groundwork Assessment towards Sustainable Urban Development for Malaysia, In: Journal of Environmental Protection, vol.4, p.38, 2013.

C. A. Vanegas, G. Daniel, B. Aliaga, and . Bene?, Building reconstruction using manhattan-world grammars, Conference on Computer Vision and Pattern Recognition, pp.358-365, 2010.

K. Vanhoey, C. E. Porto-de-oliveira, H. Riemenschneider, A. Bódis-szomorú, and S. Manén, VarCity -the Video: The Struggles and Triumphs of Leveraging Fundamental Research Results in a Graphics Video Production, ACM SIGGRAPH 2017 Talks. SIGGRAPH '17, vol.48, p.37, 2017.

V. Vapnik, The nature of statistical learning theory, p.189, 2013.

. Varduhn, R. Vasco, E. Mundani, and . Rank, Multi-resolution models: Recent progress in coupling 3D geometry to environmental numerical simulation, 3D Geoinformation Sciences, p.37, 2015.

M. Varma and B. Rakesh-babu, More generality in efficient multiple kernel learning, 26th Annual International Conference on Machine Learning, p.190, 2009.

Y. Verdie, F. Lafarge, and P. Alliez, Lod generation for urban scenes, In: ACM Transactions on Graphics, vol.76, p.61, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01113078

V. Verma, R. Kumar, and S. Hsu, 3D building detection and modeling from aerial LIDAR data, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, vol.89, p.77, 2006.

S. Vishwanathan, N. Vichy, N. Nicol, R. Schraudolph, K. M. Kondor et al., Graph kernels, In: Journal of Machine Learning Research, vol.11, pp.1201-1242, 2010.

T. Vögtle and E. Steinle, On the quality of object classification and automated building modeling based on laserscanning data, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIV.3/W13, vol.65, p.62, 2003.

P. Wate and V. Coors, 3D Data Models for Urban Energy Simulation, Energy Procedia 78. 6th International Building Physics Conference, IBPC 2015, vol.37, p.26, 2015.

B. Watson, P. Müller, O. Veryovka, A. Fuller, and P. Wonka, Procedural urban modeling in practice, IEEE Computer Graphics and Applications, vol.28, p.38, 2008.

T. Werner and A. Zisserman, New techniques for automated architectural reconstruction from photographs, European Conference on Computer Vision (ECCV), vol.72, p.61, 2002.

B. Willenborg, Simulation of explosions in urban space and result analysis based on CityGML-City Models and a cloud-based 3D-Webclient, p.40, 2015.

M. Wolff and H. Asche, Geospatial modelling of urban security: A novel approach with virtual 3D city models, International Conference on Computational Science and Its Applications, p.40, 2008.

M. Wolff and H. Asche, Towards geovisual analysis of crime scenes-a 3D crime mapping approach, Advances in GIScience, p.40, 2009.

H. Wu, Z. He, and J. Gong, A virtual globe-based 3D visualization and interactive framework for public participation in urban planning processes, p.37, 2010.

B. Xiong, S. O. Elberink, and G. Vosselman, A graph edit dictionary for correcting errors in roof topology graphs reconstructed from point clouds, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.93, p.73, 2014.

W. Yan, A. Yeung, A. Shaker, A. P. Habib, and . Kersting, Improving classification accuracy of airborne LiDAR intensity data by geometric calibration and radiometric correction, In: ISPRS Journal of Photogrammetry and Remote Sensing, vol.67, p.47, 2012.

R. You and B. Lin, A quality prediction method for building model reconstruction using LiDAR data and topographic maps, IEEE Transactions on Geoscience and Remote Sensing, vol.49, p.62, 2011.

Z. Yun, F. Magdy, S. Y. Iskander, D. Lim, R. He et al., Radio wave propagation prediction based on 3-D building structures extracted from 2-D images, IEEE Antennas and Wireless Propagation Letters, vol.6, p.37, 2007.

L. Zebedin, J. Bauer, K. Karner, and H. Bischof, Fusion of feature-and area-based information for urban buildings modeling from aerial imagery, European Conference on Computer Vision (ECCV), pp.873-886, 2008.

C. Zeng, T. Zhao, and J. Wang, A multicriteria evaluation method for 3-D building reconstruction, IEEE Geoscience and Remote Sensing Letters, vol.11, issue.9, pp.1619-1623, 2014.

H. Zeng, J. Wu, and Y. Furukawa, Neural procedural reconstruction for residential buildings, European Conference on Computer Vision (ECCV), 2018.

. Springer, , vol.66, p.63

L. Zhang, T. Qian, and Q. Zeng, The Radon measure formulation for edge detection using rotational wavelets, In: Commun. Pure Appl. Anal, vol.6, p.141, 2007.

L. Zhang and L. Zhang, Deep learning-based classification and reconstruction of residential scenes from large-scale point clouds, IEEE Transactions on Geoscience and Remote Sensing, vol.56, p.63, 2017.

Z. Zhao, H. Ledoux, and J. E. Stoter, Automatic repair of CityGML LOD2 buildings using shrink-wrapping, p.50, 2013.

Q. Zhou and U. Neumann, 2.5 d dual contouring: A robust approach to creating building models from aerial lidar point clouds, European Conference on Computer Vision (ECCV), vol.90, p.61, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01549533

L. Zhu, S. Shen, X. Gao, and Z. Hu, Large Scale Urban Scene Modeling from MVS Meshes, European Conference on Computer Vision (ECCV), 2018.

. Springer, , vol.63, pp.614-629

S. Zlatanova, A. Abdul-rahman, and M. Pilouk, Trends in 3D GIS development, In: Journal of Geospatial Engineering, vol.4, issue.2, p.40, 2002.