24.3.2.4 Building Footprints

Chapter Contents (Back)
Footprint, Building. Building Recognition. Building Footprint. Mostly intended as the 2-D region, not the 3-D description.

Rüther, H.[Heinz], Martine, H.M.[Hagai M.], Mtalo, E.G.,
Application of snakes and dynamic programming optimisation technique in modeling of buildings in informal settlement areas,
PandRS(56), No. 4, July 2002, pp. 269-282.
HTML Version. 0207
BibRef

Song, W.B.[Wen-Bo], Haithcoat, T.L.,
Development of comprehensive accuracy assessment indexes for building footprint extraction,
GeoRS(43), No. 2, February 2005, pp. 402-404.
IEEE Abstract. 0501
BibRef

Zhang, K., Yan, J., Chen, S.C.,
Automatic Construction of Building Footprints From Airborne LIDAR Data,
GeoRS(44), No. 9, September 2006, pp. 2523-2533.
IEEE DOI 0609
BibRef

Yan, J.H.[Jian-Hua], Zhang, K.Q.[Ke-Qi], Zhang, C.C.[Cheng-Cui], Chen, S.C.[Shu-Ching], Narasimhan, G.,
Automatic Construction of 3-D Building Model From Airborne LIDAR Data Through 2-D Snake Algorithm,
GeoRS(53), No. 1, January 2015, pp. 3-14.
IEEE DOI 1410
airborne radar BibRef

Gamba, P.[Paolo], Dell'Acqua, F.[Fabio], Lisini, G.[Gianni], Cisotta, F.[Francesco],
Improving Building Footprints in InSAR Data by Comparison with a Lidar DSM,
PhEngRS(72), No. 1, January 2006, pp. 63-70.
WWW Link. The combination of three-dimensional laser and radar data for improved building extraction. 0602
BibRef

Vallet, B.[Bruno], Pierrot-Deseilligny, M.[Marc], Boldo, D.[Didier], Brédif, M.[Mathieu],
Building footprint database improvement for 3D reconstruction: A split and merge approach and its evaluation,
PandRS(66), No. 5, September 2011, pp. 732-742.
Elsevier DOI 1110
BibRef
Earlier: A1, A2, A3, Only:
Building Footprint Database Improvement for 3D Reconstruction: A Direction Aware Split and Merge Approach,
CMRT09(139-144).
PDF File. 0909
Photogrammetry; Segmentation; Reconstruction; Urban scene; Building BibRef

Bredif, M., Boldo, D., Pierrot-Deseilligny, M., Maitre, H.,
3D Building Reconstruction with Parametric Roof Superstructures,
ICIP07(II: 537-540).
IEEE DOI 0709
BibRef

Tournaire, O.[Olivier], Bredif, M., Boldo, D., Durupt, M.,
An efficient stochastic approach for building footprint extraction from digital elevation models,
PandRS(65), No. 4, July 2010, pp. 317-327.
Elsevier DOI 1003
Digital Elevation Model; Building footprint; Energetic modeling; Marked point processes; RJMCMC BibRef

Brédif, M.[Mathieu], Tournaire, O.[Olivier], Vallet, B.[Bruno], Champion, N.[Nicolas],
Extracting polygonal building footprints from digital surface models: A fully-automatic global optimization framework,
PandRS(77), No. 1, March 2013, pp. 57-65.
Elsevier DOI 1303
Urban; Building; Modeling; Geometry; Analysis; DEM/DTM BibRef

Ferro, A., Brunner, D., Bruzzone, L.,
Automatic Detection and Reconstruction of Building Radar Footprints From Single VHR SAR Images,
GeoRS(51), No. 2, February 2013, pp. 935-952.
IEEE DOI 1302
Cited by 1 BibRef

Gilani, S.A.N.[Syed Ali Naqi], Awrangjeb, M.[Mohammad], Lu, G.J.[Guo-Jun],
An Automatic Building Extraction and Regularisation Technique Using LiDAR Point Cloud Data and Orthoimage,
RS(8), No. 3, 2016, pp. 258.
DOI Link 1604
BibRef
And:
Robust building roof segmentation using airborne point cloud data,
ICIP16(859-863)
IEEE DOI 1610
BibRef
And:
Fusion of LIDAR Data and Multispectral Imagery for Effective Building Detection Based on Graph and Connected Component Analysis,
PIA15(65-72).
DOI Link 1504
BibRef
And: A2, A3, Only:
A triangulation-based technique for building boundary identification from point cloud data,
ICVNZ15(1-6)
IEEE DOI 1701
BibRef
And: A2, A3, Only:
Automatic Building Footprint Extraction and Regularisation from LIDAR Point Cloud Data,
DICTA14(1-8)
IEEE DOI 1502
buildings (structures). Buildings digital elevation models
See also Automatic Extraction of Building Roofs Using LIDAR Data and Multispectral Imagery. BibRef

Dey, E.K.[Emon Kumar], Awrangjeb, M.[Mohammad], Kurdi, F.T.[Fayez Tarsha], Stantic, B.[Bela],
Building Boundary Extraction from LiDAR Point Cloud Data,
DICTA21(1-6)
IEEE DOI 2201
Point cloud compression, Measurement, Image segmentation, Laser radar, Shape, Digital images, boundary extraction, Performance metric BibRef

Awrangjeb, M., Lu, G.J.[Guo-Jun], Fraser, C.S.,
Automatic Building Extraction From LIDAR Data Covering Complex Urban Scenes,
PCV14(25-32).
DOI Link 1404
BibRef
Earlier: A1, A2, Only:
Building Roof Plane Extraction from LIDAR Data,
DICTA13(1-8)
IEEE DOI 1402
geophysical image processing BibRef

Awrangjeb, M.[Mohammad], Ravanbakhsh, M.[Mehdi], Fraser, C.S.[Clive S.],
Automatic Detection of Residential Buildings Using LIDAR Data and Multispectral Imagery,
PandRS(65), No. 5, September 2010, pp. 457-467.
Elsevier DOI 1003
BibRef
And:
Building Detection from Multispectral Imagery and LIDAR Data Employing A Threshold-Free Evaluation System,
PCVIA10(A:49).
PDF File. 1009
BibRef
And:
Automatic Building Detection Using LIDAR Data and Multispectral Imagery,
DICTA10(45-51).
IEEE DOI 1012
Building detection; LIDAR; Point cloud; Multispectral imagery; Fusion BibRef

Li, J.Z.[Jing-Zhong], Li, X.G.[Xin-Gong], Xie, T.[Tian],
Morphing of Building Footprints Using a Turning Angle Function,
IJGI(6), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Zhuo, X.Y.[Xiang-Yu], Fraundorfer, F.[Friedrich], Kurz, F.[Franz], Reinartz, P.[Peter],
Optimization of OpenStreetMap Building Footprints Based on Semantic Information of Oblique UAV Images,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Li, W.J.[Wei-Jia], He, C.H.[Cong-Hui], Fang, J.R.[Jia-Rui], Zheng, J.P.[Jue-Peng], Fu, H.H.[Hao-Huan], Yu, L.[Le],
Semantic Segmentation-Based Building Footprint Extraction Using Very High-Resolution Satellite Images and Multi-Source GIS Data,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
BibRef
Earlier: A1, A2, A3, A5, Only:
Semantic Segmentation Based Building Extraction Method Using Multi-source GIS Map Datasets and Satellite Imagery,
DeepGlobe18(233-2333)
IEEE DOI 1812
Buildings, Satellites, Urban areas, Semantics, Image segmentation, Training, Data mining BibRef

Bagheri, H.[Hossein], Schmitt, M.[Michael], Zhu, X.X.[Xiao-Xiang],
Fusion of Multi-Sensor-Derived Heights and OSM-Derived Building Footprints for Urban 3D Reconstruction,
IJGI(8), No. 4, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Schuegraf, P.[Philipp], Bittner, K.[Ksenia],
Automatic Building Footprint Extraction from Multi-Resolution Remote Sensing Images Using a Hybrid FCN,
IJGI(8), No. 4, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Bittner, K., Cui, S., Reinartz, P.,
Building Extraction From Remote Sensing Data Using Fully Convolutional Networks,
Hannover17(481-486).
DOI Link 1805
BibRef

Pasquali, G.[Giorgio], Iannelli, G.C.[Gianni Cristian], Dell'Acqua, F.[Fabio],
Building Footprint Extraction from Multispectral, Spaceborne Earth Observation Datasets Using a Structurally Optimized U-Net Convolutional Neural Network,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Liu, P.H.[Peng-Hua], Liu, X.P.[Xiao-Ping], Liu, M.X.[Meng-Xi], Shi, Q.[Qian], Yang, J.X.[Jin-Xing], Xu, X.C.[Xiao-Cong], Zhang, Y.Y.[Yuan-Ying],
Building Footprint Extraction from High-Resolution Images via Spatial Residual Inception Convolutional Neural Network,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Wei, S., Ji, S., Lu, M.,
Toward Automatic Building Footprint Delineation From Aerial Images Using CNN and Regularization,
GeoRS(58), No. 3, March 2020, pp. 2178-2189.
IEEE DOI 2003
Building extraction, fully convolutional network (FCN), polygon regularization, segmentation BibRef

Li, Q., Shi, Y., Huang, X., Zhu, X.X.,
Building Footprint Generation by Integrating Convolution Neural Network With Feature Pairwise Conditional Random Field (FPCRF),
GeoRS(58), No. 11, November 2020, pp. 7502-7519.
IEEE DOI 2011
Buildings, Semantics, Feature extraction, Image segmentation, Task analysis, Remote sensing, semantic segmentation BibRef

Sun, Y.[Yao], Montazeri, S.[Sina], Wang, Y.Y.[Yuan-Yuan], Zhu, X.X.[Xiao Xiang],
Automatic registration of a single SAR image and GIS building footprints in a large-scale urban area,
PandRS(170), 2020, pp. 1-14.
Elsevier DOI 2011
GIS building footprints, Large-scale, Registration, SAR image, Urban area BibRef

Milosavljevic, A.[Aleksandar],
Automated Processing of Remote Sensing Imagery Using Deep Semantic Segmentation: A Building Footprint Extraction Case,
IJGI(9), No. 8, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Gautam, D., Lucieer, A., Bendig, J., Malenovský, Z.,
Footprint Determination of a Spectroradiometer Mounted on an Unmanned Aircraft System,
GeoRS(58), No. 5, May 2020, pp. 3085-3096.
IEEE DOI 2005
Spectroradiometers, Global navigation satellite system, Antennas, Geology, Vegetation mapping, Cameras, Synchronization, unmanned aircraft system (UAS) BibRef

Liao, C.[Cheng], Hu, H.[Han], Li, H.F.[Hai-Feng], Ge, X.M.[Xu-Ming], Chen, M.[Min], Li, C.N.[Chuang-Nong], Zhu, Q.[Qing],
Joint Learning of Contour and Structure for Boundary-Preserved Building Extraction,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhu, Q.[Qing], Liao, C.[Cheng], Hu, H.[Han], Mei, X.M.[Xiao-Ming], Li, H.F.[Hai-Feng],
MAP-Net: Multiple Attending Path Neural Network for Building Footprint Extraction From Remote Sensed Imagery,
GeoRS(59), No. 7, July 2021, pp. 6169-6181.
IEEE DOI 2106
Feature extraction, Buildings, Semantics, Data mining, Spatial resolution, Remote sensing, Convolution, semantic segmentation BibRef

Touzani, S.[Samir], Granderson, J.[Jessica],
Open Data and Deep Semantic Segmentation for Automated Extraction of Building Footprints,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Ayala, C.[Christian], Sesma, R.[Rubén], Aranda, C.[Carlos], Galar, M.[Mikel],
A Deep Learning Approach to an Enhanced Building Footprint and Road Detection in High-Resolution Satellite Imagery,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Wei, X.C.[Xin-Chun], Li, X.[Xing], Liu, W.[Wei], Zhang, L.P.[Lian-Peng], Cheng, D.[Dayu], Ji, H.Y.[Han-Yu], Zhang, W.Z.[Wen-Zheng], Yuan, K.[Kai],
Building Outline Extraction Directly Using the U2-Net Semantic Segmentation Model from High-Resolution Aerial Images and a Comparison Study,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Li, Z.M.[Zi-Ming], Xin, Q.C.[Qin-Chuan], Sun, Y.[Ying], Cao, M.Y.[Meng-Ying],
A Deep Learning-Based Framework for Automated Extraction of Building Footprint Polygons from Very High-Resolution Aerial Imagery,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Daranagama, S.[Samitha], Witayangkurn, A.[Apichon],
Automatic Building Detection with Polygonizing and Attribute Extraction from High-Resolution Images,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Liu, C.[Chun], Hu, Y.[Yaohui], Li, Z.[Zheng], Xu, J.[Junkui], Han, Z.G.[Zhi-Gang], Guo, J.Z.[Jian-Zhong],
TriangleConv: A Deep Point Convolutional Network for Recognizing Building Shapes in Map Space,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Yan, X.F.[Xiong-Feng], Chen, H.[Huan], Huang, H.R.[Hao-Ran], Liu, Q.[Qian], Yang, M.[Min],
Building Typification in Map Generalization Using Affinity Propagation Clustering,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Wei, S.Q.[Shi-Qing], Ji, S.P.[Shun-Ping],
Graph Convolutional Networks for the Automated Production of Building Vector Maps From Aerial Images,
GeoRS(60), 2022, pp. 1-11.
IEEE DOI 2112
Buildings, Feature extraction, Remote sensing, Image segmentation, Detectors, Data mining, Production, Building extraction, polygon regularization BibRef

Guo, H.[Haonan], Du, B.[Bo], Zhang, L.P.[Liang-Pei], Su, X.[Xin],
A coarse-to-fine boundary refinement network for building footprint extraction from remote sensing imagery,
PandRS(183), 2022, pp. 240-252.
Elsevier DOI 2201
Building footprint extraction, Boundary refinement, Coarse-to-fine BibRef

Yang, H.P.[Hai-Ping], Xu, M.[Meixia], Chen, Y.Y.[Yuan-Yuan], Wu, W.[Wei], Dong, W.[Wen],
A Postprocessing Method Based on Regions and Boundaries Using Convolutional Neural Networks and a New Dataset for Building Extraction,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Li, Q.Y.[Qing-Yu], Zorzi, S.[Stefano], Shi, Y.L.[Yi-Lei], Fraundorfer, F.[Friedrich], Zhu, X.X.[Xiao Xiang],
RegGAN: An End-to-End Network for Building Footprint Generation with Boundary Regularization,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Wangiyana, S.[Sandhi], Samczynski, P.[Piotr], Gromek, A.[Artur],
Data Augmentation for Building Footprint Segmentation in SAR Images: An Empirical Study,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Hu, Y.[Yaohui], Liu, C.[Chun], Li, Z.[Zheng], Xu, J.[Junkui], Han, Z.G.[Zhi-Gang], Guo, J.Z.[Jian-Zhong],
Few-Shot Building Footprint Shape Classification with Relation Network,
IJGI(11), No. 5, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Li, Z.C.[Zhi-Chao], Zhang, S.[Shuai], Dong, J.[Jinwei],
Suggestive Data Annotation for CNN-Based Building Footprint Mapping Based on Deep Active Learning and Landscape Metrics,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Huang, Y.H.[Yu-Han], Jin, Y.F.[Yu-Fang],
Aerial Imagery-Based Building Footprint Detection with an Integrated Deep Learning Framework: Applications for Fine Scale Wildland-Urban Interface Mapping,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Li, Z.C.[Zhi-Chao], Dong, J.[Jinwei],
A Framework Integrating DeeplabV3+, Transfer Learning, Active Learning, and Incremental Learning for Mapping Building Footprints,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Li, X.[Xiao], Qiu, F.[Fang], Shi, F.[Fan], Tang, Y.W.[Yun-Wei],
A Recursive Hull and Signal-Based Building Footprint Generation from Airborne LiDAR Data,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Wang, Z.H.[Ze-Hui], Meng, Y.[Yu], Chen, J.B.[Jing-Bo], Ma, J.X.[Jun-Xian], Yue, A.Z.[An-Zhi], Chen, J.S.[Jian-Sheng],
Learning Color Distributions from Bitemporal Remote Sensing Images to Update Existing Building Footprints,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Wang, J.W.[Jin-Wang], Meng, L.X.[Ling-Xuan], Li, W.J.[Wei-Jia], Yang, W.[Wen], Yu, L.[Lei], Xia, G.S.[Gui-Song],
Learning to Extract Building Footprints From Off-Nadir Aerial Images,
PAMI(45), No. 1, January 2023, pp. 1294-1301.
IEEE DOI 2212
Buildings, Head, Training, Annotations, Task analysis, Imaging, Image segmentation, Building footprint extraction, off-nadir aerial image BibRef

Razzak, M.T.[Muhammed T.], Mateo-García, G.[Gonzalo], Lecuyer, G.[Gurvan], Gómez-Chova, L.[Luis], Gal, Y.[Yarin], Kalaitzis, F.[Freddie],
Multi-spectral multi-image super-resolution of Sentinel-2 with radiometric consistency losses and its effect on building delineation,
PandRS(195), 2023, pp. 1-13.
Elsevier DOI 2301
Super-resolution, Multi-image super-resolution, Sentinel 2, Segmentation, Building detection BibRef

Aryal, J.[Jagannath], Neupane, B.[Bipul],
Multi-Scale Feature Map Aggregation and Supervised Domain Adaptation of Fully Convolutional Networks for Urban Building Footprint Extraction,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Wei, S.Q.[Shi-Qing], Zhang, T.[Tao], Ji, S.[Shunping], Luo, M.[Muying], Gong, J.Y.[Jian-Ya],
BuildMapper: A fully learnable framework for vectorized building contour extraction,
PandRS(197), 2023, pp. 87-104.
Elsevier DOI 2303
Building contour delineation, Instance segmentation, Contour-based method, Deep learning, Remote sensing images BibRef

Chen, J.[Jing], Xia, M.[Min], Wang, D.[Dehao], Lin, H.F.[Hai-Feng],
Double Branch Parallel Network for Segmentation of Buildings and Waters in Remote Sensing Images,
RS(15), No. 6, 2023, pp. 1536.
DOI Link 2304
BibRef

Liu, Z.P.[Ze-Ping], Tang, H.[Hong],
Learning Sparse Geometric Features for Building Segmentation from Low-Resolution Remote-Sensing Images,
RS(15), No. 7, 2023, pp. 1741.
DOI Link 2304
BibRef

Ullah, T.[Tahira], Lautenbach, S.[Sven], Herfort, B.[Benjamin], Reinmuth, M.[Marcel], Schorlemmer, D.[Danijel],
Assessing Completeness of OpenStreetMap Building Footprints Using MapSwipe,
IJGI(12), No. 4, 2023, pp. 143.
DOI Link 2305
BibRef

Sakeena, M.[Muntaha], Stumpe, E.[Eric], Despotovic, M.[Miroslav], Koch, D.[David], Zeppelzauer, M.[Matthias],
On the Robustness and Generalization Ability of Building Footprint Extraction on the Example of SegNet and Mask R-CNN,
RS(15), No. 8, 2023, pp. 2135.
DOI Link 2305
BibRef

Hu, Y.[Yuan], Wang, Z.B.[Zhi-Bin], Huang, Z.[Zhou], Liu, Y.[Yu],
PolyBuilding: Polygon transformer for building extraction,
PandRS(199), 2023, pp. 15-27.
Elsevier DOI 2305
Building extraction, Polygon transformer, Polygon refinement scheme, Two-phase training strategy BibRef

Liao, C.[Cheng], Hu, H.[Han], Yuan, X.[Xuekun], Li, H.F.[Hai-Feng], Liu, C.[Chao], Liu, C.Y.[Chun-Yang], Fu, G.[Gui], Ding, Y.L.[Yu-Lin], Zhu, Q.[Qing],
BCE-Net: Reliable building footprints change extraction based on historical map and up-to-date images using contrastive learning,
PandRS(201), 2023, pp. 138-152.
Elsevier DOI 2307
Building update, Change detection, Semantic segmentation, Contrastive learning BibRef

Zhou, Z.Y.[Zhi-Yong], Fu, C.[Cheng], Weibel, R.[Robert],
Move and remove: Multi-task learning for building simplification in vector maps with a graph convolutional neural network,
PandRS(202), 2023, pp. 205-218.
Elsevier DOI 2308
Map generalization, Building simplification, Vector maps, Multi-task learning, Graph convolutional neural networks BibRef

?ura?iová, R.[Renata],
An Aggregated Shape Similarity Index: A Case Study of Comparing the Footprints of OpenStreetMap and INSPIRE Buildings,
IJGI(12), No. 12, 2023, pp. 495.
DOI Link 2312
BibRef

Kong, L.H.[Ling-Hui], Qian, H.Z.[Hai-Zhong], Wu, Y.Q.[Yu-Qing], Niu, X.Y.[Xin-Yu], Wang, D.[Di], Huang, Z.K.[Zhe-Kun],
Simplification and Regularization Algorithm for Right-Angled Polygon Building Outlines with Jagged Edges,
IJGI(12), No. 12, 2023, pp. 469.
DOI Link 2312
BibRef

Liu, J.L.[Jun-Lin], Xia, Y.[Ying], Feng, J.F.[Jiang-Fan], Bai, P.[Peng],
A Novel Building Extraction Network via Multi-Scale Foreground Modeling and Gated Boundary Refinement,
RS(15), No. 24, 2023, pp. 5638.
DOI Link 2401
BibRef

Kim, J.Y.[Ji-Yong], Kim, Y.[Yongil],
Integrated Framework for Unsupervised Building Segmentation with Segment Anything Model-Based Pseudo-Labeling and Weakly Supervised Learning,
RS(16), No. 3, 2024, pp. 526.
DOI Link 2402
BibRef


Zhang, M.M.[Ming-Ming], Liu, Q.J.[Qing-Jie], Wang, W.[Wei], Wang, Y.H.[Yun-Hong],
Transbuilding: An End-to-End Polygonal Building Extraction with Transformers,
ICIP23(460-464)
IEEE DOI 2312
BibRef

Zhao, Y.[Yao], Wang, G.X.[Guang-Xia], Yang, J.[Jian], Zhang, L.[Lantian], Qi, X.F.[Xiao-Fei],
Building Block Extraction from Historical Maps Using Deep Object Attention Networks,
IJGI(11), No. 11, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zorzi, S.[Stefano], Bazrafkan, S.[Shabab], Habenschuss, S.[Stefan], Fraundorfer, F.[Friedrich],
PolyWorld: Polygonal Building Extraction with Graph Neural Networks in Satellite Images,
CVPR22(1838-1847)
IEEE DOI 2210
Image segmentation, Satellites, Codes, Computer network reliability, Buildings, Predictive models, grouping and shape analysis BibRef

Xu, Z.Q.[Zi-Qiang], Xu, C.Y.[Chun-Yan], Cui, Z.[Zhen], Zheng, X.W.[Xiang-Wei], Yang, J.[Jian],
CVNet: Contour Vibration Network for Building Extraction,
CVPR22(1373-1381)
IEEE DOI 2210
Vibrations, Shape, Computational modeling, Buildings, Transforms, Feature extraction, Mathematical models, Segmentation, grouping and shape analysis BibRef

Chen, J.[Jun], Jiang, Y.X.[Yu-Xuan], Luo, L.[Linbo], Gu, Y.[Yue], Wu, K.[Kangle],
Building Footprint Generation by Integrating U-Net with Deepened Space Module,
ICIP21(3847-3851)
IEEE DOI 2201
Training, Image segmentation, Image resolution, Splicing, Image edge detection, Buildings, Robustness, deep learning, high resolution image BibRef

Girard, N.[Nicolas], Smirnov, D.[Dmitriy], Solomon, J.[Justin], Tarabalka, Y.[Yuliya],
Polygonal Building Extraction by Frame Field Learning,
CVPR21(5887-5896)
IEEE DOI 2111
Training, Image segmentation, Shape, Buildings, Prediction algorithms, Skeleton, Task analysis BibRef

Ashiotis, G.[Giannis], Oldfield, J.[James], Chrysostomou, C.[Charalambos], Christoudias, T.[Theodoros], Nicolaou, M.A.[Mihalis A.],
Shared-space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views,
PRRS20 (536-549).
Springer DOI 2103
BibRef

Bischke, B., Helber, P., Folz, J., Borth, D., Dengel, A.,
Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks,
ICIP19(1480-1484)
IEEE DOI 1910
Deep Learning, Semantic Segmentation, Satellite Imagery, Multi Task Learning, Building Extraction BibRef

Khoshboresh Masouleh, M., Saradjian, M.R.,
Robust Building Footprint Extraction From Big Multi-sensor Data Using Deep Competition Network,
SMPR19(615-621).
DOI Link 1912
BibRef

Dickenson, M., Gueguen, L.,
Rotated Rectangles for Symbolized Building Footprint Extraction,
DeepGlobe18(215-2153)
IEEE DOI 1812
Buildings, Microprocessors, Architecture, Urban areas, Satellites BibRef

Linh, T.H.[Truong-Hong], Laefer, D.F.[Debra F.], Yang, B.S.[Bi-Sheng], Huang, R.G.[Rong-Gang], Li, J.P.[Jian-Ping],
IQPC 2015 Track: Evaluation of Automatically Generated 2D Footprints from Urban Lidar Data,
GeoBigData15(527-534).
DOI Link 1602
BibRef

Li, Y., Zhu, L., Shimamura, H., Tachibana, K.,
A Refining Method For Building Object Aggregation And Footprint Modelling Using Multi-source Data,
ISPRS12(XXXIX-B3:41-46).
DOI Link 1209
BibRef

Dini, G.R., Jacobsen, K., Heipke, C.,
Delineation of Building Footprints from High Resolution Satellite Stereo Imagery Using Image Matching and a GIS Database,
Hannover13(81-85).
DOI Link 1308

See also 3D Building Change Detection Using High Resolution Stereo Images and a GIS Database.
See also procedure for semi-Automatic Orthophoto Generation from High Resolution Satellite Imagery, A. BibRef

Michelin, J.C., Mallet, C., David, N.,
Building Edge Detection Using Small-footprint Airborne Full-waveform Lidar Data,
AnnalsPRS(I-3), No. 2012, pp. 147-152.
DOI Link 1209
BibRef

Yan, L.[Lili], Zhang, J.X.[Ji-Xian], Huang, G.[Guoman], Zhao, Z.[Zheng],
Building Footprints Extraction from PolSAR Image Using Multi-Features and Edge Information,
ISIDF11(1-5).
IEEE DOI 1111
BibRef

Wang, O.[Oliver], Lodha, S.K.[Suresh K.], Helmbold, D.P.[David P.],
A Bayesian Approach to Building Footprint Extraction from Aerial LIDAR Data,
3DPVT06(192-199).
IEEE DOI 0606
BibRef

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Roof Structure, 3-D .


Last update:Feb 29, 2024 at 09:13:14