Jordan, M.,
Cocquerez, J.P.,
3-Dimensional Description of Scenes Observed in Aerial-Photography,
PR(28), No. 7, July 1995, pp. 931-947.
Elsevier DOI
BibRef
9507
Paparoditis, N.,
Cord, M.,
Jordan, M.,
Cocquerez, J.P.,
Building Detection and Reconstruction from
Mid- and High-resolution Aerial Imagery,
CVIU(72), No. 2, November 1998, pp. 122-142.
DOI Link
BibRef
9811
Cord, M.[Matthieu],
Jordan, M.[Michel],
Cocquerez, J.P.[Jean-Pierre],
Accurate Building Structure Recovery from High Resolution Aerial
Imagery,
CVIU(82), No. 2, May 2001, pp. 138-173.
DOI Link
0108
Adaptive Stereo.
Stereo, Computation. Gradient correlation, contour-adaptive windows with a geodesic weighting,
a multi- resolution coarse to fine scheme, and a
two-way filtering symmetrical validation.
BibRef
Iovan, C.[Corina],
Boldo, D.[Didier],
Cord, M.[Matthieu],
Erikson, M.[Mats],
Automatic Extraction and Classification of Vegetation Areas from High
Resolution Images in Urban Areas,
SCIA07(858-867).
Springer DOI
0706
BibRef
And: A1, A2, A3, Only:
Detection, Segmentation and Characterization of Vegetation in
High-Resolution Aerial Images for 3D City Modeling,
ISPRS08(B3a: 247 ff).
PDF File.
0807
BibRef
Cord, M.[Matthieu],
Jordan, M.[Michel],
Cocquerez, J.P.[Jean-Pierre],
Paparoditis, N.[Nicolas],
Automatic Extraction and Modelling of Urban Buildings from High
Resolution Aerial Images,
ISPRSGIS99(187-192).
Compute a DEM using edge information -- the weight is iversely proportional
to the distance
to the center without crossing an edge. If the edges are complete
then the weight is zero in these regions. Thus the correlation only
applies in the actual region so the boundaries are sharper.
Then generate rectangles from the data.
BibRef
9900
Jordan, M.[Michel],
Cord, M.[Matthieu],
Belli, T.[Thomas],
Building Detection from High Resolution Digital Elevation Models in
Urban Areas,
PCV02(B: 96).
0305
BibRef
Cord, M.,
Belli, T.,
Terrain surface modeling from altimetric data,
ICIP02(III: 809-812).
IEEE DOI
0210
BibRef
Belli, T.,
Cord, M.,
Jordan, M.,
3D Data Reconstruction and Modeling for Urban Scene Analysis,
Ascona01(125-134).
From color images. Model terrain as parametric surface to get above ground
regions (i.e. the buildings).
0201
BibRef
Kim, T.J.[Tae-Jung],
Muller, J.P.A.[Jan-Peter A.],
A Technique for 3D Building Reconstruction,
PhEngRS(64), No. 9, September 1998, pp. 923-930.
9809
BibRef
Kim, T.J.[Tae-Jung],
Muller, J.P.A.[Jan-Peter A.],
Automated Urban Area Building Extraction from
High-Resolution Stereo Imagery,
IVC(14), No. 2, March 1996, pp. 115-130.
Elsevier DOI
9607
BibRef
Kim, T.J.[Tae-Jung],
Muller, J.P.A.[Jan-Peter A.],
Building Extraction and Verification from Spaceborne and Aerial
Imagery Using Image Understanding Fusion Techniques,
Ascona95(221-230).
BibRef
9500
And:
Automated Building Height Estimation and Object Extraction from
Multiresolution Imagery,
SPIE(2486), 1995, pp. 267-276.
BibRef
Kim, T.J.[Tae-Jung],
Muller, J.P.A.[Jan-Peter A.],
Development of a graph-based approach for building detection,
IVC(17), No. 1, January 1999, pp. 3-14.
Elsevier DOI
BibRef
9901
Kim, T.J.[Tae-Jung],
Semiautomatic Building Line Extraction from Ikonos Images Through
Monoscopic Line Analysis,
PhEngRS(72), No. 5, May 2006, pp. 541-550.
WWW Link.
0610
A new algorithm for extracting building lines from monoscopic
high-resolution satellite images.
See also Extraction of digital elevation models from satellite stereo images through stereo matching based on epipolarity and scene geometry.
BibRef
Fraser, C.S.,
Baltsavias, E.,
Gruen, A.,
Processing of Ikonos imagery for submetre 3D positioning and building
extraction,
PandRS(56), No. 3, April 2002, pp. 177-194.
HTML Version.
0205
BibRef
Earlier:
3D Building Reconstruction from High-Resolution Ikonos Stereo-Imagery,
Ascona01(331-344).
Evaluate geopositioning accuracy, radiometric quality.
Submeter is possible. But variability between images may limit
applicibility.
0201
BibRef
Fraser, C.S.,
Evolution of network orientation procedures,
IEVM06(xx-yy).
PDF File.
0609
BibRef
Jin, X.Y.[Xiao-Ying],
Davis, C.H.[Curt H.],
Automated Building Extraction from High-Resolution Satellite Imagery in
Urban Areas Using Structural, Contextual, and Spectral Information,
JASP(2005), No. 14, 2005, pp. 2196-2206.
WWW Link.
0603
See also High-Resolution DEMs for Urban Applications from NAPP Photography.
BibRef
Hermosilla, T.[Txomin],
Ruiz, L.A.[Luis A.],
Recio, J.A.[Jorge A.],
Estornell, J.[Javier],
Evaluation of Automatic Building Detection Approaches Combining
High Resolution Images and LiDAR Data,
RS(3), No. 6, 2011, pp. 1188-1210.
DOI Link
1204
BibRef
Hermosilla, T.[Txomin],
Automatic building detection and land use classification in urban areas
using multispectral high-spatial resolution imagery and LiDAR data,
ELCVIA(13), No. 2, 2014, pp. xx-yy.
DOI Link
1407
BibRef
Shaker, I.,
Abd-Elrahman, A.,
Abdel-Gawad, A.,
Sherief, M.,
Building Extraction from High Resolution Space Images in High Density
Residential Areas in the Great Cairo Region,
RS(3), No. 4, April 2011, pp. 781-791.
DOI Link
1203
BibRef
Freire, S.,
Santos, T.,
Navarro, A.,
Soares, F.,
Silva, J.D.,
Afonso, N.,
Fonseca, A.,
Tenedório, J.,
Introducing Mapping Standards in the Quality Assessment of Buildings
Extracted from Very High Resolution Satellite Imagery,
PandRS(90), No. 1, 2014, pp. 1-9.
Elsevier DOI
1404
Evaluation, Building Extraction. QuickBird
BibRef
Li, Z.B.[Zhong-Bin],
Shi, W.Z.[Wen-Zhong],
Wang, Q.M.[Qun-Ming],
Miao, Z.L.[Ze-Lang],
Extracting Man-Made Objects From High Spatial Resolution Remote
Sensing Images via Fast Level Set Evolutions,
GeoRS(53), No. 2, February 2015, pp. 883-899.
IEEE DOI
1411
BibRef
And:
Correction:
GeoRS(53), No. 10, October 2015, pp. 5794-5794.
IEEE DOI
1509
Gaussian processes
BibRef
Xu, Y.Y.[Yong-Yang],
Wu, L.[Liang],
Xie, Z.[Zhong],
Chen, Z.L.[Zhan-Long],
Building Extraction in Very High Resolution Remote Sensing Imagery
Using Deep Learning and Guided Filters,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link
1802
BibRef
Chen, R.X.[Ren-Xi],
Li, X.H.[Xin-Hui],
Li, J.[Jonathan],
Object-Based Features for House Detection from RGB High-Resolution
Images,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Yang, H.[Hui],
Wu, P.H.[Peng-Hai],
Yao, X.D.[Xue-Dong],
Wu, Y.L.[Yan-Lan],
Wang, B.[Biao],
Xu, Y.Y.[Yong-Yang],
Building Extraction in Very High Resolution Imagery by
Dense-Attention Networks,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Sun, G.Y.[Gen-Yun],
Huang, H.[Hui],
Zhang, A.Z.[Ai-Zhu],
Li, F.[Feng],
Zhao, H.M.[Hui-Min],
Fu, H.[Hang],
Fusion of Multiscale Convolutional Neural Networks for Building
Extraction in Very High-Resolution Images,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Ma, W.X.[Wei-Xuan],
Wan, Y.C.[You-Chuan],
Li, J.Y.[Jia-Yi],
Zhu, S.[Sa],
Wang, M.W.[Ming-Wei],
An Automatic Morphological Attribute Building Extraction Approach for
Satellite High Spatial Resolution Imagery,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Bi, Q.[Qi],
Qin, K.[Kun],
Zhang, H.[Han],
Zhang, Y.[Ye],
Li, Z.L.[Zhi-Li],
Xu, K.[Kai],
A Multi-Scale Filtering Building Index for Building Extraction in
Very High-Resolution Satellite Imagery,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Pan, X.[Xuran],
Yang, F.[Fan],
Gao, L.[Lianru],
Chen, Z.C.[Zheng-Chao],
Zhang, B.[Bing],
Fan, H.[Hairui],
Ren, J.C.[Jin-Chang],
Building Extraction from High-Resolution Aerial Imagery Using a
Generative Adversarial Network with Spatial and Channel Attention
Mechanisms,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Ye, Z.R.[Zi-Ran],
Fu, Y.Y.[Yong-Yong],
Gan, M.[Muye],
Deng, J.S.[Jin-Song],
Comber, A.[Alexis],
Wang, K.[Ke],
Building Extraction from Very High Resolution Aerial Imagery Using
Joint Attention Deep Neural Network,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Jing, W.P.[Wei-Peng],
Lin, J.B.[Jing-Bo],
Wang, H.H.[Hui-Hui],
Building NAS: Automatic designation of efficient neural architectures
for building extraction in high-resolution aerial images,
IVC(103), 2020, pp. 104025.
Elsevier DOI
2011
Convolutional neural network, Deep learning, Aerial images,
Semantic segmentation, Neural architecture search
BibRef
Zhu, Q.Q.[Qi-Qi],
Li, Z.[Zhen],
Zhang, Y.N.[Ya-Nan],
Guan, Q.F.[Qing-Feng],
Building Extraction from High Spatial Resolution Remote Sensing
Images via Multiscale-Aware and Segmentation-Prior Conditional Random
Fields,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Chen, M.[Meng],
Wu, J.J.[Jian-Jun],
Liu, L.Z.[Lei-Zhen],
Zhao, W.H.[Wen-Hui],
Tian, F.[Feng],
Shen, Q.[Qiu],
Zhao, B.Y.[Bing-Yu],
Du, R.H.[Ruo-Hua],
DR-Net: An Improved Network for Building Extraction from High
Resolution Remote Sensing Image,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Wang, C.[Chao],
Zhang, Y.[Yan],
Chen, X.H.[Xiao-Hui],
Jiang, H.[Hao],
Mukherjee, M.[Mithun],
Wang, S.[Shuai],
Automatic Building Detection from High-Resolution Remote Sensing
Images Based on Joint Optimization and Decision Fusion of
Morphological Attribute Profiles,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link
2102
BibRef
Jin, Y.W.[Yu-Wei],
Xu, W.B.[Wen-Bo],
Zhang, C.[Ce],
Luo, X.[Xin],
Jia, H.T.[Hai-Tao],
Boundary-Aware Refined Network for Automatic Building Extraction in
Very High-Resolution Urban Aerial Images,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Guo, H.[Haonan],
Shi, Q.[Qian],
Du, B.[Bo],
Zhang, L.P.[Liang-Pei],
Wang, D.Z.[Dong-Zhi],
Ding, H.X.[Hua-Xiang],
Scene-Driven Multitask Parallel Attention Network for Building
Extraction in High-Resolution Remote Sensing Images,
GeoRS(59), No. 5, May 2021, pp. 4287-4306.
IEEE DOI
2104
BibRef
And:
Correction:
GeoRS(59), No. 6, June 2021, pp. 5387-5387.
IEEE DOI
2106
Buildings, Feature extraction, Remote sensing, Data mining,
Task analysis, Semantics, Optical imaging,
scene driven
BibRef
Yang, B.J.[Bing-Jie],
Huang, Y.C.[Yuan-Cheng],
Su, X.[Xin],
Guo, H.[Haonan],
MAEANet: Multiscale Attention and Edge-Aware Siamese Network for
Building Change Detection in High-Resolution Remote Sensing Images,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Guo, H.[Haonan],
Su, X.[Xin],
Wu, C.[Chen],
Du, B.[Bo],
Zhang, L.P.[Liang-Pei],
SAAN: Similarity-Aware Attention Flow Network for Change Detection
With VHR Remote Sensing Images,
IP(33), 2024, pp. 2599-2613.
IEEE DOI
2404
Feature extraction, Decoding, Task analysis, Semantics, Optimization,
Remote sensing, Correlation, Remote sensing image,
attention mechanism
BibRef
Ran, S.H.[Shu-Hao],
Gao, X.J.[Xian-Jun],
Yang, Y.W.[Yuan-Wei],
Li, S.H.[Shao-Hua],
Zhang, G.B.[Guang-Bin],
Wang, P.[Ping],
Building Multi-Feature Fusion Refined Network for Building Extraction
from High-Resolution Remote Sensing Images,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Seong, S.[Seonkyeong],
Choi, J.[Jaewan],
Semantic Segmentation of Urban Buildings Using a High-Resolution
Network (HRNet) with Channel and Spatial Attention Gates,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Xia, L.G.[Lie-Gang],
Zhang, J.X.[Jun-Xia],
Zhang, X.B.[Xiong-Bo],
Yang, H.P.[Hai-Ping],
Xu, M.X.[Mei-Xia],
Precise Extraction of Buildings from High-Resolution Remote-Sensing
Images Based on Semantic Edges and Segmentation,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Fang, F.[Fang],
Wu, K.S.[Kai-Shun],
Liu, Y.Y.[Yuan-Yuan],
Li, S.W.[Sheng-Wen],
Wan, B.[Bo],
Chen, Y.L.[Yan-Ling],
Zheng, D.Y.[Dao-Yuan],
A Coarse-to-Fine Contour Optimization Network for Extracting Building
Instances from High-Resolution Remote Sensing Imagery,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Liu, Y.Y.[Yuan-Yuan],
Chen, D.Y.[Ding-Yuan],
Ma, A.L.[Ai-Long],
Zhong, Y.F.[Yan-Fei],
Fang, F.[Fang],
Xu, K.[Kai],
Multiscale U-Shaped CNN Building Instance Extraction Framework With
Edge Constraint for High-Spatial-Resolution Remote Sensing Imagery,
GeoRS(59), No. 7, July 2021, pp. 6106-6120.
IEEE DOI
2106
Buildings, Feature extraction, Image segmentation, Semantics,
Remote sensing, Image edge detection, Proposals, Deep learning,
multiscale building extraction
BibRef
Wen, X.[Xiang],
Li, X.[Xing],
Zhang, C.[Ce],
Han, W.Q.[Wen-Quan],
Li, E.[Erzhu],
Liu, W.[Wei],
Zhang, L.P.[Lian-Peng],
ME-Net: A Multi-Scale Erosion Network for Crisp Building Edge
Detection from Very High Resolution Remote Sensing Imagery,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Zhang, T.[Tao],
Tang, H.[Hong],
Ding, Y.[Yi],
Li, P.L.[Peng-Long],
Ji, C.[Chao],
Xu, P.L.[Peng-Lei],
FSRSS-Net: High-Resolution Mapping of Buildings from
Middle-Resolution Satellite Images Using a Super-Resolution Semantic
Segmentation Network,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Gui, S.X.[Sheng-Xi],
Qin, R.J.[Rong-Jun],
Automated LoD-2 model reconstruction from very-high-resolution
satellite-derived digital surface model and orthophoto,
PandRS(181), 2021, pp. 1-19.
Elsevier DOI
2110
LoD-2 Building Modeling, Data-driven,
Decomposition and merging, Multi-stereo satellite images
BibRef
Ferrari, L.[Luca],
Dell'Acqua, F.[Fabio],
Zhang, P.[Peng],
Du, P.J.[Pei-Jun],
Integrating EfficientNet into an HAFNet Structure for Building
Mapping in High-Resolution Optical Earth Observation Data,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Ding, L.[Lei],
Tang, H.[Hao],
Liu, Y.H.[Ya-Hui],
Shi, Y.L.[Yi-Lei],
Zhu, X.X.[Xiao Xiang],
Bruzzone, L.[Lorenzo],
Adversarial Shape Learning for Building Extraction in VHR Remote
Sensing Images,
IP(31), 2022, pp. 678-690.
IEEE DOI
2201
Buildings, Shape, Image segmentation, Feature extraction,
Adversarial machine learning, Semantics,
remote sensing
BibRef
Wang, Y.[Yong],
Zeng, X.Q.[Xiang-Qiang],
Liao, X.H.[Xiao-Han],
Zhuang, D.F.[Da-Fang],
B-FGC-Net: A Building Extraction Network from High Resolution Remote
Sensing Imagery,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Hosseinpour, H.[Hamidreza],
Samadzadegan, F.[Farhad],
Javan, F.D.[Farzaneh Dadrass],
CMGFNet: A deep cross-modal gated fusion network for building
extraction from very high-resolution remote sensing images,
PandRS(184), 2022, pp. 96-115.
Elsevier DOI
2202
Building extraction, VHR remote sensing image,
Digital surface model, Gated fusion module, Cross-modal
BibRef
Li, J.H.[Jian-Hao],
Zhuang, Y.[Yin],
Dong, S.[Shan],
Gao, P.[Peng],
Dong, H.[Hao],
Chen, H.[He],
Chen, L.[Liang],
Li, L.L.[Lian-Lin],
Hierarchical Disentangling Network for Building Extraction from Very
High Resolution Optical Remote Sensing Imagery,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Chen, J.Z.[Jin-Zhi],
Zhang, D.J.[De-Jun],
Wu, Y.Q.[Yi-Qi],
Chen, Y.L.[Yi-Lin],
Yan, X.H.[Xiao-Hu],
A Context Feature Enhancement Network for Building Extraction from
High-Resolution Remote Sensing Imagery,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Manos, E.[Elias],
Witharana, C.[Chandi],
Udawalpola, M.R.[Mahendra Rajitha],
Hasan, A.[Amit],
Liljedahl, A.K.[Anna K.],
Convolutional Neural Networks for Automated Built Infrastructure
Detection in the Arctic Using Sub-Meter Spatial Resolution Satellite
Imagery,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Hossain, M.D.[Mohammad D.],
Chen, D.M.[Dong-Mei],
A hybrid image segmentation method for building extraction from
high-resolution RGB images,
PandRS(192), 2022, pp. 299-314.
Elsevier DOI
2209
Image segmentation, Hybrid method, Building extraction, GEOBIA
BibRef
Wang, C.S.[Chun-Shan],
Sun, W.[Wei],
Wu, H.R.[Hua-Rui],
Zhao, C.J.[Chun-Jiang],
Teng, G.[Guifa],
Yang, Y.R.[Ying-Ru],
Du, P.F.[Peng-Fei],
A Low-Altitude Remote Sensing Inspection Method on Rural Living
Environments Based on a Modified YOLOv5s-ViT,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
For scattered rural buildings.
BibRef
Feng, D.[Dan],
Chu, H.Y.[Hong-Yun],
Zheng, L.[Ling],
Frequency Spectrum Intensity Attention Network for Building Detection
from High-Resolution Imagery,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Bai, H.W.[Hai-Wei],
Cheng, J.[Jian],
Su, Y.Z.[Yan-Zhou],
Wang, Q.[Qi],
Han, H.R.[Hao-Ran],
Zhang, Y.J.[Yi-Jie],
Multi-Branch Adaptive Hard Region Mining Network for Urban Scene
Parsing of High-Resolution Remote-Sensing Images,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Xu, G.[Gang],
Deng, M.[Min],
Sun, G.[Geng],
Guo, Y.[Ya],
Chen, J.[Jie],
Improving Building Extraction by Using Knowledge Distillation to
Reduce the Impact of Label Noise,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
He, Y.[Yong],
Liao, W.T.[Wen-Ting],
Hong, H.[Hao],
Huang, X.[Xu],
High-Precision Single Building Model Reconstruction Based on the
Registration between OSM and DSM from Satellite Stereos,
RS(15), No. 5, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Wang, Z.Q.[Zhen-Qing],
Zhou, Y.[Yi],
Wang, F.[Futao],
Wang, S.X.[Shi-Xin],
Qin, G.[Gang],
Zou, W.J.[Wei-Jie],
Zhu, J.F.[Jin-Feng],
A Multi-Scale Edge Constraint Network for the Fine Extraction of
Buildings from Remote Sensing Images,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Yan, G.[Geding],
Jing, H.T.[Hai-Tao],
Li, H.[Hui],
Guo, H.[Huanchao],
He, S.[Shi],
Enhancing Building Segmentation in Remote Sensing Images: Advanced
Multi-Scale Boundary Refinement with MBR-HRNet,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link
2308
BibRef
Xu, B.[Bowen],
Xu, J.[Jiakun],
Xue, N.[Nan],
Xia, G.S.[Gui-Song],
HiSup: Accurate polygonal mapping of buildings in satellite imagery
with hierarchical supervision,
PandRS(198), 2023, pp. 284-296.
Elsevier DOI
2304
Building extraction, Building vectorization, High-resolution satellite imagery
BibRef
Li, W.J.[Wei-Jia],
Zhao, W.Q.[Wen-Qian],
Yu, J.H.[Jin-Hua],
Zheng, J.P.[Jue-Peng],
He, C.H.[Cong-Hui],
Fu, H.H.[Hao-Huan],
Lin, D.[Dahua],
Joint semantic-geometric learning for polygonal building segmentation
from high-resolution remote sensing images,
PandRS(201), 2023, pp. 26-37.
Elsevier DOI
2307
Building extraction, Semantic segmentation,
Graph neural networks, High-resolution remote sensing images
BibRef
Xie, Y.K.[Ya-Kun],
Feng, D.J.[De-Jun],
Xiong, S.[Sifan],
Zhu, J.[Jun],
Liu, Y.G.[Yang-Ge],
Multi-Scene Building Height Estimation Method Based on Shadow in High
Resolution Imagery,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link
2108
BibRef
Wang, X.D.[Xu-Dong],
Tian, M.L.[Ming-Liang],
Zhang, Z.J.[Zhi-Jun],
He, K.[Kang],
Wang, S.[Sheng],
Liu, Y.[Yan],
Dong, Y.[Yusen],
SDSNet: Building Extraction in High-Resolution Remote Sensing Images
Using a Deep Convolutional Network with Cross-Layer Feature
Information Interaction Filtering,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link
2401
BibRef
Hossain, M.D.[Mohammad D.],
Chen, D.M.[Dong-Mei],
Performance Comparison of Deep Learning (DL)-Based Tabular Models for
Building Mapping Using High-Resolution Red, Green, and Blue Imagery
and the Geographic Object-Based Image Analysis Framework,
RS(16), No. 5, 2024, pp. 878.
DOI Link
2403
BibRef
Du, Z.T.[Zhuo-Tong],
Sui, H.G.[Hai-Gang],
Zhou, Q.M.[Qi-Ming],
Zhou, M.T.[Ming-Ting],
Shi, W.[Weiyue],
Wang, J.X.[Jian-Xun],
Liu, J.Y.[Jun-Yi],
Vectorized building extraction from high-resolution remote sensing
images using spatial cognitive graph convolution model,
PandRS(213), 2024, pp. 53-71.
Elsevier DOI
2406
Building extraction, High-resolution remote sensing images,
Shape encoding, Graph convolutional networks, Graph pooling
BibRef
He, Z.Y.[Zhi-Yi],
Yao, W.[Wei],
Shao, J.[Jie],
Wang, P.[Puzuo],
UB-FineNet: Urban building fine-grained classification network for
open-access satellite images,
PandRS(217), 2024, pp. 76-90.
Elsevier DOI Code:
WWW Link.
2409
Urban buildings, Satellite images, Fine-grained classification,
Super-resolution, Deep learning
BibRef
Gao, J.L.[Jia-Liang],
Zhang, B.[Bin],
Wu, Y.T.[Yun-Tao],
Guo, C.[Chang],
Building Extraction from High Resolution Remote Sensing Images Based
on Improved Mask R-CNN,
ICRVC22(1-6)
IEEE DOI
2301
Deep learning, Image segmentation, Image resolution, Buildings,
Feature extraction, Robot sensing systems, attention mechanism
BibRef
Liu, L.Y.,
Wang, C.K.,
Building Segmentation in Agricultural Land Using High Resolution
Satellite Imagery Based on Deep Learning Approach,
ISPRS21(B3-2021: 587-594).
DOI Link
2201
BibRef
Ding, Y.[Yi],
Wu, M.Y.[Mu-Yu],
Xu, Y.S.[Yong-Shu],
Duan, S.J.[Song-Jiang],
P-Linknet: Linknet with Spatial Pyramid Pooling for High-resolution
Satellite Imagery,
ISPRS20(B3:35-40).
DOI Link
2012
BibRef
Kong, F.,
Huang, B.,
Bradbury, K.,
Malof, J.M.,
The Synthinel-1 dataset: a collection of high resolution synthetic
overhead imagery for building segmentation,
WACV20(1803-1812)
IEEE DOI
2006
Buildings, Image segmentation, Benchmark testing, Training, Cameras,
Software, Urban areas
BibRef
Hosseinpoor, H.R.,
Samadzadegan, F.,
Attention Based Convolutional Neural Network for Building Extraction
From Very High Resolution Remote Sensing Image,
SMPR19(507-512).
DOI Link
1912
BibRef
Barragán, W.,
Campos, A.,
Sanchez, G.,
Automatic Generation Of Building Mapping Using Digital, Vertical And
Aerial High Resolution Photographs And Lidar Point Clouds,
ISPRS16(B7: 171-176).
DOI Link
1610
BibRef
Rechichi, F.,
Mandelli, A.,
Achille, C.,
Fassi, F.,
Sharing High-resolution Models And Information On Web:
The Web Module Of Bim3dsg System,
ISPRS16(B5: 703-710).
DOI Link
1610
BibRef
Quattrini, R.,
Malinverni, E.S.,
Clini, P.,
Nespeca, R.,
Orlietti, E.,
From TLS To HBIM. High Quality Semantically-Aware 3D Modeling of
Complex Architecture,
3D-Arch15(367-374).
DOI Link
1504
BibRef
Silván-Cárdenas, J.L.[José Luis],
Almazán-González, J.A.[Juan Andrés],
Couturier, S.A.[Stéphane A.],
Remote Identification of Housing Buildings with High-Resolution Remote
Sensing,
MCPR14(380-390).
Springer DOI
1407
BibRef
Souri, A.H.,
Mohammadi, A.,
Sharifi, M.A.,
A New Prompt for Building Extraction in High Resolution Remotely Sensed
Imagery,
SMPR13(405-408).
DOI Link
1311
BibRef
Guo, Z.,
Luo, L.,
Wang, W.,
Du, S.,
Data fusion of high-resolution satellite imagery and GIS data for
automatic building extraction,
IWIDF13(23-28).
DOI Link
1311
BibRef
Sun, X.[Xian],
Thiele, A.,
Hinz, S.[Stefan],
Fu, K.,
Automatic Detection and Recognition of Man-Made Objects in High
Resolution Remote Sensing Images Using Hierarchical Semantic Graph
Model,
Hannover13(333-338).
DOI Link
1308
BibRef
Attarzadeh, R.,
Momeni, M.,
Object-based Building Extraction from High Resolution Satellite Imagery,
ISPRS12(XXXIX-B4:57-60).
DOI Link
1209
BibRef
Elouedi, I.[Ines],
Hamouda, A.[Atef],
Rojbani, H.[Hmida],
Rectangular Discrete Radon Transform for Buildings Extraction from High
Resolution Satellite Images,
ICIAR12(I: 418-426).
Springer DOI
1206
BibRef
Zhao, J.[Jun],
Ning, X.G.[Xiao-Gang],
Zhang, J.X.[Ji-Xian],
A Detection Method of New Buildings Based on High Resolution Remote
Images,
ISIDF11(1-4).
IEEE DOI
1111
BibRef
Krauß, T.[Thomas],
Reinartz, P.[Peter],
Refinement of Urban Digital Elevation Models from Very High Resolution
Stereo Satellite Images,
HighRes09(xx-yy).
PDF File.
0906
BibRef
Krauß, T.[Thomas],
Lehner, M.[Manfred],
Reinartz, P.[Peter],
Generation of COARSE 3D Models of Urban Areas from High Resolution
Stereo Satellite Image,
ISPRS08(B1: 1091 ff).
PDF File.
0807
BibRef
Krauß, T.,
Reinartz, P.,
Stilla, U.,
Extracting Orthogonal Building Objects in Urban Areas from High
Resolution Stereo Satellite Image Pairs,
PIA07(77).
PDF File.
0711
Classify as building -- rectangular shapes, tree, and terrain.
BibRef
Krauß, T.[Thomas],
Preprocessing of Satellite Data for Urban Object Extraction,
PIA15(115-120).
DOI Link
1504
BibRef
Mayer, S.,
Gradient based splitting of blocks of houses in high-resolution
ortho-images,
ICIP02(I: 769-772).
IEEE DOI
0210
BibRef
Earlier:
Constrained Optimization of Building Contours from High-resolution
Ortho-images,
ICIP01(I: 838-841).
IEEE DOI
0108
BibRef
Canu, D.[David],
Gambotto, J.P.[Jean-Pierre],
Sirat, J.A.[Jacques Ariel],
Ayache, N.,
Reconstruction of Buildings from Multiple High Resolution Images,
ICIP96(II: 621-624).
IEEE DOI
BibRef
9600
Berthod, M.,
Gabet, L.,
Giraudon, G., and
Lotti, J.L.,
High-Resolution Stereo for the Detection of Buildings,
Ascona95(135-144).
Generate a DEM with buildings, then extract the buildings from the
DEM.
BibRef
9500
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Buildings from Depth Data, LiDAR Data .