24.3.6.2 Building Interiors, Walls, Indoor Models

Chapter Contents (Back)
Indoor Models. Interior Models.
See also Indoor Navigation Issues, Lines, Walls, Doors, Flat Surfaces.
See also Building Facades, Ground Level Images.
See also Floorplans, Floor Plans, Building Interiors.
See also Room Layout. Navigation possible:
See also Vision-Language Navigation.

NYU Depth Dataset V2,

HTML Version. Dataset, RGBD. Dataset, Indoor Scenes.
See also Indoor Segmentation and Support Inference from RGBD Images.

El-Hakim, S.F.[Sabry F.], Boulanger, P.[Pierre],
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Mudure, M.[Mihai], Popescu, V.[Voicu],
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VC(24), No. 7-9, July 2008, pp. xx-yy.
Springer DOI 0804
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Bahmutov, G.[Gleb], Popescu, V.[Voicu], Mudure, M.[Mihai],
Efficient large scale acquisition of building interiors,
SigGraph06(Article 127).
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Lin, L., Zeng, K., Wang, Y., Hu, W.,
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Sareen, K.K.[Kuldeep K.], Knopf, G.K.[George K.], Canas, R.[Roberto],
Hierarchical data clustering approach for segmenting colored three-dimensional point clouds of building interiors,
OptEng(50), No. 7, 2011, pp. 077003.
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Knopf, G.K.[George K.], Sareen, K.K.[Kuldeep K.], Canas, R.[Roberto],
Reconstructing complex scenes for virtual reality,
SPIE(Newsroom), October 20, 2011
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A robust data segmentation strategy for large colorized point clouds of building interiors improves modeling of scanned space. BibRef

Lien, J.M.[Jyh-Ming], Camelli, F.[Fernando], Wong, D.[David], Lu, Y.Y.[Yan-Yan], McWhorter, B.[Benjamin],
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Lagunas, E., Amin, M.G., Ahmad, F., Najar, M.,
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GeoRS(51), No. 2, February 2013, pp. 891-906.
IEEE DOI 1302
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Wang, R.[Rong], Wang, Z.L.[Zhi-Liang], Ma, X.R.[Xi-Rong],
Indoor Scene Classification Based on the Bag-of-Words Model of Local Feature Information Gain,
IEICE(E96-D), No. 4, April 2013, pp. 984-987.
WWW Link. 1304
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Liu, H.[Han], Yang, Y.L.[Yong-Liang], Al Halawani, S.[Sawsan], Mitra, N.J.[Niloy J.],
Constraint-aware interior layout exploration for pre-cast concrete-based buildings,
VC(29), No. 6-8, June 2013, pp. 663-673.
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Keller, F.[Friedrich], Sternberg, H.[Harald],
Multi-Sensor Platform for Indoor Mobile Mapping: System Calibration and Using a Total Station for Indoor Applications,
RS(5), No. 11, 2013, pp. 5805-5824.
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Oesau, S.[Sven], Lafarge, F.[Florent], Alliez, P.[Pierre],
Indoor scene reconstruction using feature sensitive primitive extraction and graph-cut,
PandRS(90), No. 1, 2014, pp. 68-82.
Elsevier DOI 1404
Award, U.V. Helava, ISPRS. Indoor scenes BibRef

Pintore, G.[Giovanni], Gobbetti, E.[Enrico],
Effective mobile mapping of multi-room indoor structures,
VC(30), No. 6-8, June 2014, pp. 707-716.
WWW Link. 1407
BibRef

Leigsnering, M., Amin, M., Ahmad, F., Zoubir, A.,
Multipath Exploitation and Suppression for SAR Imaging of Building Interiors: An overview of recent advances,
SPMag(31), No. 4, July 2014, pp. 110-119.
IEEE DOI 1407
Buildings BibRef

Shoaib, M.[Muhammad], Yang, M.Y.[Michael Ying], Rosenhahn, B.[Bodo], Ostermann, J.[Joern],
Estimating layout of cluttered indoor scenes using trajectory-based priors,
IVC(32), No. 11, 2014, pp. 870-883.
Elsevier DOI 1410
Scene segmentation BibRef

Lehtola, V.V.[Ville V.], Virtanen, J.P.[Juho-Pekka], Kukko, A.[Antero], Kaartinen, H.[Harri], Hyyppä, H.[Hannu],
Localization of mobile laser scanner using classical mechanics,
PandRS(99), No. 1, 2015, pp. 25-29.
Elsevier DOI 1502
Indoor. No inertial sensors. Mobile BibRef

Gupta, S.[Saurabh], Arbeláez, P.[Pablo], Girshick, R.[Ross], Malik, J.[Jitendra],
Indoor Scene Understanding with RGB-D Images: Bottom-up Segmentation, Object Detection and Semantic Segmentation,
IJCV(112), No. 2, April 2015, pp. 133-149.
Springer DOI 1504
BibRef
Earlier: A1, A3, A2, A4:
Learning Rich Features from RGB-D Images for Object Detection and Segmentation,
ECCV14(VII: 345-360).
Springer DOI 1408
BibRef
Earlier: A1, A2, A4, Only:
Perceptual Organization and Recognition of Indoor Scenes from RGB-D Images,
CVPR13(564-571)
IEEE DOI 1309
RGBD Recognition; RGBD Segmentation
See also Simultaneous Detection and Segmentation. BibRef

Girshick, R.[Ross], Donahue, J.[Jeff], Darrell, T.J.[Trevor J.], Malik, J.[Jitendra],
Region-Based Convolutional Networks for Accurate Object Detection and Segmentation,
PAMI(38), No. 1, January 2016, pp. 142-158.
IEEE DOI 1601
BibRef
Earlier:
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation,
CVPR14(580-587)
IEEE DOI 1409
Detectors BibRef

Rosser, J.[Julian], Morley, J.[Jeremy], Smith, G.[Gavin],
Modelling of Building Interiors with Mobile Phone Sensor Data,
IJGI(4), No. 2, 2015, pp. 989.
DOI Link 1507
BibRef

Thomson, C.[Charles], Boehm, J.[Jan],
Automatic Geometry Generation from Point Clouds for BIM,
RS(7), No. 9, 2015, pp. 11753.
DOI Link 1511
BibRef
Earlier:
Indoor Modelling Benchmark for 3D Geometry Extraction,
CloseRange14(581-587).
DOI Link 1411
BibRef

Chen, A.Y., Huang, T.[Ting],
Toward BIM-Enabled Decision Making for In-Building Response Missions,
ITS(16), No. 5, October 2015, pp. 2765-2773.
IEEE DOI 1511
building materials BibRef

Park, S.J.[Seong-Jin], Hong, K.S.[Ki-Sang],
Video semantic object segmentation by self-adaptation of DCNN,
PRL(112), 2018, pp. 249-255.
Elsevier DOI 1809
Video semantic segmentation, Video object segmentation, Deep convolutional neural network BibRef

Romero-González, C.[Cristina], Martínez-Gómez, J.[Jesus], García-Varea, I.[Ismael], Rodríguez-Ruiz, L.[Luis],
3D Spatial Pyramid: Descriptors generation from point clouds for indoor scene classification,
MVA(27), No. 2, February 2016, pp. 263-273.
Springer DOI 1602
BibRef

Khan, S.H.[Salman H.], Bennamoun, M.[Mohammed], Sohel, F.A.[Ferdous A.], Togneri, R.[Roberto], Naseem, I.[Imran],
Integrating Geometrical Context for Semantic Labeling of Indoor Scenes using RGBD Images,
IJCV(117), No. 1, March 2016, pp. 1-20.
Springer DOI 1604
BibRef
Earlier: A1, A2, A3, A4, Only:
Geometry Driven Semantic Labeling of Indoor Scenes,
ECCV14(I: 679-694).
Springer DOI 1408
RGBD data. BibRef

Khan, S.H.[Salman H.], Hayat, M.[Munawar], Bennamoun, M.[Mohammed], Togneri, R.[Roberto], Sohel, F.A.[Ferdous A.],
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition,
IP(25), No. 7, July 2016, pp. 3372-3383.
IEEE DOI 1606
convolution BibRef

Pintore, G.[Giovanni], Ganovelli, F.[Fabio], Gobbetti, E.[Enrico], Scopigno, R.[Roberto],
Mobile Mapping and Visualization of Indoor Structures to Simplify Scene Understanding and Location Awareness,
ACVR16(II: 130-145).
Springer DOI 1611
BibRef

Quintana, B., Prieto, S.A., Adán, A., Vázquez, A.S.,
Autonomous Scanning of Structural Elements in Buildings,
CIARP16(60-67).
Springer DOI 1703
BibRef

Loch-Dehbi, S.[Sandra], Dehbi, Y.[Youness], Plümer, L.[Lutz],
Estimation of 3D Indoor Models with Constraint Propagation and Stochastic Reasoning in the Absence of Indoor Measurements,
IJGI(6), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Thomas, D.[Diego], Sugimoto, A.[Akihiro],
Modeling large-scale indoor scenes with rigid fragments using RGB-D cameras,
CVIU(157), No. 1, 2017, pp. 103-116.
Elsevier DOI 1704
3D Modeling BibRef

Kim, S., Manduchi, R.[Roberto],
Multi-planar Fitting in an Indoor Manhattan World,
WACV17(11-19)
IEEE DOI 1609
Cameras, Clustering algorithms, Computational modeling, Data models, Estimation, Geometry, Robustness BibRef

Hofer, M.[Manuel], Maurer, M.[Michael], Bischof, H.[Horst],
Efficient 3D scene abstraction using line segments,
CVIU(157), No. 1, 2017, pp. 167-178.
Elsevier DOI 1704
BibRef
Earlier:
Line3D: Efficient 3D Scene Abstraction for the Built Environment,
GCPR15(237-248).
Springer DOI 1511
Structure-from-Motion BibRef

Günther, M.[Martin], Wiemann, T.[Thomas], Albrecht, S.[Sven], Hertzberg, J.[Joachim],
Model-based furniture recognition for building semantic object maps,
AI(247), No. 1, 2017, pp. 336-351.
Elsevier DOI 1705
Semantic, map BibRef

Kang, H.K.[Hae-Kyong], Li, K.J.[Ki-Joune],
A Standard Indoor Spatial Data Model: OGC IndoorGML and Implementation Approaches,
IJGI(6), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Jung, J.[Jaehoon], Stachniss, C.[Cyrill], Kim, C.J.[Chang-Jae],
Automatic Room Segmentation of 3D Laser Data Using Morphological Processing,
IJGI(6), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Lehtola, V.V.[Ville V.], Kaartinen, H.[Harri], Nüchter, A.[Andreas], Kaijaluoto, R.[Risto], Kukko, A.[Antero], Litkey, P.[Paula], Honkavaara, E.[Eija], Rosnell, T.[Tomi], Vaaja, M.T.[Matti T.], Virtanen, J.P.[Juho-Pekka], Kurkela, M.[Matti], El Issaoui, A.[Aimad], Zhu, L.L.[Ling-Li], Jaakkola, A.[Anttoni], Hyyppä, J.[Juha],
Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Liu, M.M.[Ming-Ming], Guo, Y.[Yanwen], Wang, J.[Jun],
Indoor scene modeling from a single image using normal inference and edge features,
VC(33), No. 10, October 2017, pp. 1227-1240.
WWW Link. 1709
BibRef

Michailidis, G.T.[Georgios-Tsampikos], Pajarola, R.[Renato],
Bayesian graph-cut optimization for wall surfaces reconstruction in indoor environments,
VC(33), No. 10, October 2017, pp. 1347-1355.
WWW Link. 1709
BibRef

Zakhor, A.[Avideh],
Fast, automated 3D modeling of building interiors,
SPIE(Newsroom), September 21, 2017.
DOI Link 1711
A mapping and visualization platform for 3D modeling and documentation of indoor environments. BibRef

Liu, Y.[Yuan], Wang, J.[Jun], Song, J.W.[Jing-Wei], Song, Z.[Zihui],
Globally Consistent Indoor Mapping via a Decoupling Rotation and Translation Algorithm Applied to RGB-D Camera Output,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Lin, Z.Y.[Zhi-Yong], Xu, Z.M.[Zhi-Min], Hu, D.[Dan], Hu, Q.[Qinwu], Li, W.J.[Wen-Jing],
Hybrid Spatial Data Model for Indoor Space: Combined Topology and Grid,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Jiao, J.[Jichao], Yuan, L.[Libin], Tang, W.H.[Wei-Hua], Deng, Z.L.[Zhong-Liang], Wu, Q.[Qi],
A Post-Rectification Approach of Depth Images of Kinect v2 for 3D Reconstruction of Indoor Scenes,
IJGI(6), No. 11, 2017, pp. xx-yy.
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RGB-D. BibRef

Liu, X.B.[Xiao-Bai], Zhao, Y.B.[Yi-Biao], Zhu, S.C.[Song-Chun],
Single-View 3D Scene Reconstruction and Parsing by Attribute Grammar,
PAMI(40), No. 3, March 2018, pp. 710-725.
IEEE DOI 1802
BibRef
Earlier:
Single-View 3D Scene Parsing by Attributed Grammar,
CVPR14(684-691)
IEEE DOI 1409
Buildings, Cameras, Grammar, Image reconstruction, Semantics, scene parsing. 3d;attributed grammar;scene parsing BibRef

Zhao, Y.B.[Yi-Biao], Zhu, S.C.[Song-Chun],
Scene Parsing by Integrating Function, Geometry and Appearance Models,
CVPR13(3119-3126)
IEEE DOI 1309
affordance Indoor functional objects. BibRef

Chen, C.[Chi], Yang, B.S.[Bi-Sheng], Song, S.[Shuang], Tian, M.[Mao], Li, J.P.[Jian-Ping], Dai, W.X.[Wen-Xia], Fang, L.[Lina],
Calibrate Multiple Consumer RGB-D Cameras for Low-Cost and Efficient 3D Indoor Mapping,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
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Chen, C.[Chi], Yang, B.S.[Bi-Sheng], Song, S.[Shuang],
Low Cost And Efficient 3d Indoor Mapping Using Multiple Consumer Rgb-d Cameras,
ISPRS16(B1: 169-174).
DOI Link 1610
BibRef

Lau, L.[Lawrence], Quan, Y.M.[Yi-Ming], Wan, J.J.[Jing-Jing], Zhou, N.[Ning], Wen, C.H.[Cong-Hua], Qian, N.[Nie], Jing, F.[Faming],
An Autonomous Ultra-Wide Band-Based Attitude and Position Determination Technique for Indoor Mobile Laser Scanning,
IJGI(7), No. 4, 2018, pp. xx-yy.
DOI Link 1805
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He, F.N.[Fang-Ning], Habib, A.[Ayman],
Three-point-based solution for automated motion parameter estimation of a multi-camera indoor mapping system with planar motion constraint,
PandRS(142), 2018, pp. 278-291.
Elsevier DOI 1807
Motion estimation, Relative orientation, Multi-camera, Structure from motion, Bundle adjustment, Indoor mapping BibRef

Wang, C.[Cheng], Hou, S.W.[Shi-Wei], Wen, C.[Chenglu], Gong, Z.[Zheng], Li, Q.[Qing], Sun, X.T.[Xiao-Tian], Li, J.[Jonathan],
Semantic line framework-based indoor building modeling using backpacked laser scanning point cloud,
PandRS(143), 2018, pp. 150-166.
Elsevier DOI 1808
Point clouds, Indoor modeling, Mobile laser scanning, Line framework extraction, Semantic labeling BibRef

Li, L.[Lin], Su, F.[Fei], Yang, F.[Fan], Zhu, H.H.[Hai-Hong], Li, D.L.[Da-Lin], Zuo, X.K.[Xin-Kai], Li, F.[Feng], Liu, Y.[Yu], Ying, S.[Shen],
Reconstruction of Three-Dimensional (3D) Indoor Interiors with Multiple Stories via Comprehensive Segmentation,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
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Zhao, P.C.[Peng-Cheng], Hu, Q.W.[Qing-Wu], Wang, S.H.[Shao-Hua], Ai, M.Y.[Ming-Yao], Mao, Q.Z.[Qing-Zhou],
Panoramic Image and Three-Axis Laser Scanner Integrated Approach for Indoor 3D Mapping,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
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Pang, Y.Y.[Yue-Yong], Zhang, C.[Chi], Zhou, L.C.[Liang-Chen], Lin, B.X.[Bing-Xian], Lv, G.N.[Guo-Nian],
Extracting Indoor Space Information in Complex Building Environments,
IJGI(7), No. 8, 2018, pp. xx-yy.
DOI Link 1809
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Ren, Y.Z.[Yu-Zhuo], Chen, C.[Chen], Li, S.W.[Shang-Wen], Kuo, C.C.J.[C.C. Jay],
Context-Assisted 3D (C3D) Object Detection from RGB-D Images,
JVCIR(55), 2018, pp. 131-141.
Elsevier DOI 1809
3D Object Detection, Indoor Scene Understanding, Convolutional Neural Network, Conditional Random Field BibRef

Poux, F.[Florent], Neuville, R.[Romain], Nys, G.A.[Gilles-Antoine], Billen, R.[Roland],
3D Point Cloud Semantic Modelling: Integrated Framework for Indoor Spaces and Furniture,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
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Tabkha, A., Hajji, R., Billen, R., Poux, F.,
Semantic Enrichment of Point Cloud By Automatic Extraction And Enhancement of 360° Panoramas,
LC3D19(355-362).
DOI Link 1912
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Nikoohemat, S.[Shayan], Peter, M.[Michael], Oude Elberink, S.[Sander], Vosselman, G.[George],
Semantic Interpretation of Mobile Laser Scanner Point Clouds in Indoor Scenes Using Trajectories,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
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Elseicy, A.[Ahmed], Nikoohemat, S.[Shayan], Peter, M.[Michael], Oude Elberink, S.[Sander],
Space Subdivision of Indoor Mobile Laser Scanning Data Based on the Scanner Trajectory,
RS(10), No. 11, 2018, pp. xx-yy.
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Ding, Y.L.[You-Li], Zheng, X.W.[Xian-Wei], Zhou, Y.[Yan], Xiong, H.J.[Han-Jiang], Gong, J.Y.[Jian-Ya],
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RS(11), No. 1, 2018, pp. xx-yy.
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Semantic Geometric Modelling of Unstructured Indoor Point Cloud,
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Tran, H., Khoshelham, K., Kealy, A.,
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Elsevier DOI 1903
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Karam, S.[Samer], Vosselman, G.[George], Peter, M.[Michael], Hosseinyalamdary, S.[Siavash], Lehtola, V.[Ville],
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Liu, T., Wei, Y., Zhao, Y., Liu, S., Wei, S.,
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IP(28), No. 9, Sep. 2019, pp. 4219-4232.
IEEE DOI 1908
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Springer DOI 1908
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Tran, H.[Ha], Khoshelham, K.[Kourosh],
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PandRS(171), 2021, pp. 367-384.
Elsevier DOI 2012
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Gong, Z., Li, J., Luo, Z., Wen, C., Wang, C., Zelek, J.,
Mapping and Semantic Modeling of Underground Parking Lots Using a Backpack LiDAR System,
ITS(22), No. 2, February 2021, pp. 734-746.
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Zou, C.H.[Chu-Hang], Su, J.W.[Jheng-Wei], Peng, C.H.[Chi-Han], Colburn, A.[Alex], Shan, Q.[Qi], Wonka, P.[Peter], Chu, H.K.[Hung-Kuo], Hoiem, D.[Derek],
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Springer DOI 2105
BibRef

Huan, L.X.[Lin-Xi], Zheng, X.W.[Xian-Wei], Tang, S.J.[Sheng-Jun], Gong, J.Y.[Jian-Ya],
Learning deep cross-scale feature propagation for indoor semantic segmentation,
PandRS(176), 2021, pp. 42-53.
Elsevier DOI 2106
Indoor scene parsing, Semantic segmentation, Deep learning, Cross-scale feature propagation BibRef

Han, J.L.[Jia-Li], Rong, M.Q.[Meng-Qi], Jiang, H.Q.[Han-Qing], Liu, H.M.[Hong-Min], Shen, S.H.[Shu-Han],
Vectorized indoor surface reconstruction from 3D point cloud with multistep 2D optimization,
PandRS(177), 2021, pp. 57-74.
Elsevier DOI 2106
Indoor reconstruction, Vectorized model, Multistep 2D optimization, LoD, Semantic segmentation BibRef

Fang, H.[Hao], Pan, C.[Cihui], Huang, H.[Hui],
Structure-aware indoor scene reconstruction via two levels of abstraction,
PandRS(178), 2021, pp. 155-170.
Elsevier DOI 2108
Indoor scene reconstruction, Point cloud, Mesh processing, Primitive detection, Space partitioning, Markov random field, Surface reconstruction BibRef

Li, C.[Chang], Guan, T.R.[Tian-Rong], Yang, M.[Meng], Zhang, C.[Ce],
Combining data-and-model-driven 3D modelling (CDMD3DM) for small indoor scenes using RGB-D data,
PandRS(180), 2021, pp. 1-13.
Elsevier DOI 2109
Combining data-and-model-driven 3D modelling (CDMD3DM), Indoor scene, RGB-D, Generalized point photogrammetry, Instance segmentation BibRef

Hübner, P.[Patrick], Weinmann, M.[Martin], Wursthorn, S.[Sven], Hinz, S.[Stefan],
Automatic voxel-based 3D indoor reconstruction and room partitioning from triangle meshes,
PandRS(181), 2021, pp. 254-278.
Elsevier DOI 2110
Indoor reconstruction, 3D, Triangle mesh, Voxelization, Classification, Evaluation, Benchmark data, Microsoft HoloLens BibRef

Wang, Y.[Yu], Zhang, Z.X.[Zhen-Xin], Zhong, R.F.[Ruo-Fei], Sun, L.[Lan], Leng, S.Y.[Si-Yi], Wang, Q.[Qiang],
Densely connected graph convolutional network for joint semantic and instance segmentation of indoor point clouds,
PandRS(182), 2021, pp. 67-77.
Elsevier DOI 2112
Indoor point clouds, Joint semantic and instance segmentation, Dense connection, Graph convolutional network, Deep learning BibRef

Zhao, J., Zhang, X., Wang, Y.,
Indoor 3d Point Clouds Semantic Segmentation Bases on Modified Pointnet Network,
ISPRS20(B2:369-373).
DOI Link 2012
BibRef

Kim, H.S.[Han-Sung], Remaggi, L.[Luca], Fowler, S.[Sam], Jackson, P.J.[Philip JB], Hilton, A.[Adrian],
Acoustic Room Modelling Using 360 Stereo Cameras,
MultMed(23), 2021, pp. 4117-4130.
IEEE DOI 2112
Acoustics, Cameras, Geometry, Semantics, Image reconstruction, Estimation, Indoor geometry reconstruction, Geometrical acoustics BibRef

Chen, J.J.[Jun-Jie], Niu, L.[Li], Zhang, L.Q.[Li-Qing],
Depth Privileged Scene Recognition via Dual Attention Hallucination,
IP(30), 2021, pp. 9164-9178.
IEEE DOI 2112
Modulation, Feature extraction, Training, Image recognition, Convolution, Sun, Computer science, Indoor scene recognition, attention transfer BibRef

Yang, F.[Fan], Che, M.L.[Ming-Liang], Zuo, X.K.[Xin-Kai], Li, L.[Lin], Zhang, J.[Jiyi], Zhang, C.[Chi],
Volumetric Representation and Sphere Packing of Indoor Space for Three-Dimensional Room Segmentation,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Hübner, P.[Patrick], Weinmann, M.[Martin], Wursthorn, S.[Sven], Hinz, S.[Stefan],
Pose Normalization of Indoor Mapping Datasets Partially Compliant with the Manhattan World Assumption,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Cheng, D.Y.[Dong-Yang], Zhang, J.C.[Jun-Chao], Zhao, D.J.[Dang-Jun], Chen, J.L.[Jian-Lai], Tian, D.[Di],
Automatic Extraction of Indoor Structural Information from Point Clouds,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhang, Z.H.[Zheng-Hua], Chen, G.L.[Guo-Liang], Wang, X.[Xuan], Shu, M.C.[Ming-Cong],
Fore-Net: Efficient inlier estimation network for large-scale indoor scenario,
PandRS(184), 2022, pp. 165-176.
Elsevier DOI 2202
Inlier estimation, Low-overlapping point cloud registration, Indoor scenario, Point cloud denoising BibRef

Huan, L.X.[Lin-Xi], Zheng, X.W.[Xian-Wei], Gong, J.Y.[Jian-Ya],
GeoRec: Geometry-enhanced semantic 3D reconstruction of RGB-D indoor scenes,
PandRS(186), 2022, pp. 301-314.
Elsevier DOI 2203
Indoor 3D modeling, Semantic reconstruction, Deep learning, RGB-D scene BibRef

Chen, P.X.[Peng-Xin], Luo, Z.P.[Zhi-Peng], Shi, W.Z.[Wen-Zhong],
Hysteretic mapping and corridor semantic modeling using mobile LiDAR systems,
PandRS(186), 2022, pp. 267-284.
Elsevier DOI 2203
Hysteretic mobile mapping, Feature equalizer, Semantic modeling BibRef

Wei, Y.[Yi], Guo, H.[Hengkai], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Iterative Feature Matching for Self-Supervised Indoor Depth Estimation,
CirSysVideo(32), No. 6, June 2022, pp. 3839-3852.
IEEE DOI 2206
Estimation, Feature extraction, Image reconstruction, Training, Pipelines, Indoor environment, Optimization, feature matching BibRef

Zhu, Z.J.[Zun-Jie], Xu, Z.F.[Zhe-Feng], Chen, R.L.[Ruo-Lin], Wang, T.Y.[Ting-Yu], Wang, C.[Can], Yan, C.G.[Cheng-Gang], Xu, F.[Feng],
FastFusion: Real-Time Indoor Scene Reconstruction with Fast Sensor Motion,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Wang, T.F.[Teng-Fei], Wang, Q.[Qingdong], Ai, H.B.[Hai-Bin], Zhang, L.[Li],
Semantics-and-Primitives-Guided Indoor 3D Reconstruction from Point Clouds,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Bian, J.W.[Jia-Wang], Zhan, H.Y.[Huang-Ying], Wang, N.Y.[Nai-Yan], Chin, T.J.[Tat-Jun], Shen, C.H.[Chun-Hua], Reid, I.D.[Ian D.],
Auto-Rectify Network for Unsupervised Indoor Depth Estimation,
PAMI(44), No. 12, December 2022, pp. 9802-9813.
IEEE DOI 2212
Cameras, Videos, Training, Geometry, Estimation, Unsupervised learning, Single-view depth estimation, unsupervised learning, image rectification BibRef

Gao, Z.[Ziren], Shen, Y.[Yi], Ma, J.S.[Jing-Song], Shen, J.[Jie], Zheng, J.[Jing],
Automatic Clustering of Indoor Area Features in Shopping Malls,
IJGI(12), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Ren, D.R.[Dong-Ran], Yang, M.[Meng], Wu, J.F.[Jiang-Fan], Zheng, N.N.[Nan-Ning],
Surface normal and Gaussian weight constraints for indoor depth structure completion,
PR(138), 2023, pp. 109362.
Elsevier DOI 2303
Depth structure completion, Surface normal, Gaussian weight, Convolution neural network, Markov random field, Kernel least-square method BibRef

Cai, G.[Guoray], Pan, Y.[Yimu],
Automated Generation of Room Usage Semantics from Point Cloud Data,
IJGI(12), No. 10, 2023, pp. 427.
DOI Link 2311
BibRef

Tan, Y.[Yi], Liu, X.[Xin], Jin, S.[Shuaishuai], Wang, Q.[Qian], Wang, D.[Daochu], Xie, X.F.[Xiao-Feng],
A Terrestrial Laser Scanning-Based Method for Indoor Geometric Quality Measurement,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Cho, S.[Seonmin], Kwak, S.[Seungheon], Lee, S.[Seongwook],
Instantaneous Extraction of Indoor Environment from Radar Sensor-Based Mapping,
RS(16), No. 3, 2024, pp. 574.
DOI Link 2402
BibRef

Li, M.F.[Ming-Fan], Li, M.L.[Ming-Lei], Xu, L.[Li], Wei, M.Q.[Ming-Qiang],
Hybrid 3D Reconstruction of Indoor Scenes Integrating Object Recognition,
RS(16), No. 4, 2024, pp. 638.
DOI Link 2402
BibRef

Wang, X.[Xu], Kong, W.F.[Wei-Feng], Zhang, Q.[Qiudan], Yang, Y.[You], Zhao, T.S.[Tie-Song], Jiang, J.M.[Jian-Min],
Distortion-Aware Self-Supervised Indoor 360° Depth Estimation via Hybrid Projection Fusion and Structural Regularities,
MultMed(26), 2024, pp. 3998-4011.
IEEE DOI 2402
Estimation, Feature extraction, Distortion, Training, Self-supervised learning, Image reconstruction, Task analysis, structural regularity BibRef

Guan, F.[Fangli], Liu, J.[Jiakang], Zhang, J.H.[Jian-Hui], Yan, L.Q.[Li-Qi], Jiang, L.[Ling],
Planar Reconstruction of Indoor Scenes from Sparse Views and Relative Camera Poses,
RS(16), No. 9, 2024, pp. 1616.
DOI Link 2405
BibRef

Hu, D.C.[Ding-Chang], Chen, S.[Siang], Yang, H.Z.[Hua-Zhong], Wang, G.J.[Gui-Jin],
Query-Guided Support Prototypes for Few-Shot 3D Indoor Segmentation,
CirSysVideo(34), No. 6, June 2024, pp. 4202-4213.
IEEE DOI 2406
Prototypes, Point cloud compression, Feature extraction, Training, Data mining, Annotations, Few-shot, 3D point cloud, semantic-aware data augmentation BibRef

Guo, X.T.[Xiao-Tong], Zhao, H.J.[Hui-Jie], Shao, S.W.[Shu-Wei], Li, X.D.[Xu-Dong], Zhang, B.C.[Bao-Chang], Li, N.[Na],
SIM-MultiDepth: Self-Supervised Indoor Monocular Multi-Frame Depth Estimation Based on Texture-Aware Masking,
RS(16), No. 12, 2024, pp. 2221.
DOI Link 2406
BibRef

Feng, X.L.[Xue-Lei], Cheng, J.Z.[Jia-Zheng], Chen, S.[Simiao], Shen, Y.[Yong],
Room Impulse Response Reconstruction Using Pattern-Coupled Sparse Bayesian Learning With Spherical Waves,
SPLetters(31), 2024, pp. 1925-1929.
IEEE DOI 2408
Bayes methods, Time-domain analysis, Dictionaries, Buildings, Surface reconstruction, Pressure measurement, Noise measurement, variational inference BibRef

Lv, C.[Chen], Han, C.[Chenggong], Lang, J.[Jochen], Jiang, H.[He], Cheng, D.Q.[De-Qiang], Qian, J.S.[Jian-Sheng],
GDM-depth: Leveraging global dependency modelling for self-supervised indoor depth estimation,
IVC(149), 2024, pp. 105160.
Elsevier DOI 2408
Indoor depth estimation, Self-supervision, Global dependency modelling, Tree filter, Transformer BibRef

Shrestha, S.[Sulabh], Li, Y.M.[Yi-Meng], Košecka, J.[Jana],
Self-Supervised Pre-Training for Semantic Segmentation in an Indoor Scene,
Pretrain24(625-635)
IEEE DOI 2404
Training, Solid modeling, Semantic segmentation, Semantics, Self-supervised learning, Predictive models BibRef

Li, H.[Haoda], Yi, P.[Puyuan], Liu, Y.H.[Yun-Hao], Zahor, A.[Avideh],
Scalable MAV Indoor Reconstruction with Neural Implicit Surfaces,
CVAAD23(1536-1544)
IEEE DOI 2401
BibRef

Dong, M.Y.[Ming-Yue], Huan, L.[Linxi], Xiong, H.J.[Han-Jiang], Shen, S.H.[Shu-Han], Zheng, X.W.[Xian-Wei],
Shape Anchor Guided Holistic Indoor Scene Understanding,
ICCV23(21859-21869)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wang, Z.Q.[Zi-Qi], Luo, F.[Fei], Long, X.X.[Xiao-Xiao], Zhang, W.X.[Wen-Xiao], Xiao, C.X.[Chun-Xia],
Learning Long-range Information with Dual-Scale Transformers for Indoor Scene Completion,
ICCV23(18523-18533)
IEEE DOI 2401
BibRef

Li, Z.Z.[Zi-Zhang], Lyu, X.Y.[Xiao-Yang], Ding, Y.Y.[Yuan-Yuan], Wang, M.M.[Meng-Meng], Liao, Y.[Yiyi], Liu, Y.[Yong],
RICO: Regularizing the Unobservable for Indoor Compositional Reconstruction,
ICCV23(17715-17725)
IEEE DOI Code:
WWW Link. 2401
BibRef

Dai, Y.H.[Yu-Hui], Zhang, J.[Junkang], Fang, F.[Faming], Zhang, G.X.[Gui-Xu],
Indoor Depth Recovery Based on Deep Unfolding with Non-Local Prior,
ICCV23(12321-12330)
IEEE DOI 2401
BibRef

Vavilala, V.[Vaibhav], Forsyth, D.[David],
Convex Decomposition of Indoor Scenes,
ICCV23(9142-9152)
IEEE DOI 2401
BibRef

Yeshwanth, C.[Chandan], Liu, Y.C.[Yueh-Cheng], Nießner, M.[Matthias], Dai, A.[Angela],
ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes,
ICCV23(12-22)
IEEE DOI 2401
BibRef

Yin, R.H.[Rui-Hong], Karaoglu, S.[Sezer], Gevers, T.[Theo],
Geometry-guided Feature Learning and Fusion for Indoor Scene Reconstruction,
ICCV23(3629-3638)
IEEE DOI 2401
BibRef

Liang, Z.H.[Zhi-Hao], Huang, Z.J.[Zhang-Jin], Ding, C.X.[Chang-Xing], Jia, K.[Kui],
HelixSurf: A Robust and Efficient Neural Implicit Surface Learning of Indoor Scenes with Iterative Intertwined Regularization,
CVPR23(13165-13174)
IEEE DOI 2309
BibRef

Chang, W.J.[Wen-Jie], Zhang, Y.[Yueyi], Xiong, Z.W.[Zhi-Wei],
Depth Estimation from Indoor Panoramas with Neural Scene Representation,
CVPR23(899-908)
IEEE DOI 2309
BibRef

Gomez, A.[Alan], Rilling, S.[Stefan], Herpers, R.[Rainer],
Superquadric Indoor Scene Representation for Orientation and Navigation Tasks,
ICPR22(3692-3698)
IEEE DOI 2212
Point cloud compression, Solid modeling, Image segmentation, Navigation, Shape, Linear programming BibRef

Sayed, M.[Mohamed], Gibson, J.[John], Watson, J.[Jamie], Prisacariu, V.A.[Victor A.], Firman, M.[Michael], Godard, C.[Clément],
SimpleRecon: 3D Reconstruction Without 3D Convolutions,
ECCV22(XXXIII:1-19).
Springer DOI 2211

WWW Link. BibRef

Chen, H.X.[Hao-Xiang], Huang, J.[Jiahui], Mu, T.J.[Tai-Jiang], Hu, S.M.[Shi-Min],
CIRCLE: Convolutional Implicit Reconstruction and Completion for Large-Scale Indoor Scene,
ECCV22(XXXII:506-522).
Springer DOI 2211
BibRef

Wang, J.[Jiepeng], Wang, P.[Peng], Long, X.X.[Xiao-Xiao], Theobalt, C.[Christian], Komura, T.[Taku], Liu, L.J.[Ling-Jie], Wang, W.P.[Wen-Ping],
NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priors,
ECCV22(XXXII:139-155).
Springer DOI 2211
BibRef

Liu, H.L.[Hao-Lin], Zheng, Y.J.[Yu-Jian], Chen, G.Y.[Guan-Ying], Cui, S.G.[Shu-Guang], Han, X.G.[Xiao-Guang],
Towards High-Fidelity Single-View Holistic Reconstruction of Indoor Scenes,
ECCV22(I:429-446).
Springer DOI 2211
BibRef

Roberts, M.[Mike], Ramapuram, J.[Jason], Ranjan, A.[Anurag], Kumar, A.[Atulit], Bautista, M.A.[Miguel Angel], Paczan, N.[Nathan], Webb, R.[Russ], Susskind, J.M.[Joshua M.],
Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding,
ICCV21(10892-10902)
IEEE DOI 2203
Training, Image segmentation, Costs, Computational modeling, Semantics, Datasets and evaluation, Scene analysis and understanding BibRef

Li, B.Y.[Bo-Ying], Huang, Y.[Yuan], Liu, Z.[Zeyu], Zou, D.P.[Dan-Ping], Yu, W.X.[Wen-Xian],
StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation,
ICCV21(12643-12653)
IEEE DOI 2203
Training, Codes, Estimation, Benchmark testing, Predictive models, 3D from a single image and shape-from-x, Stereo, 3D from multiview and other sensors BibRef

Katzir, O.[Oren], Lischinski, D.[Dani], Cohen-Or, D.[Daniel],
Shape-Pose Disentanglement Using SE(3)-Equivariant Vector Neurons,
ECCV22(III:468-484).
Springer DOI 2211
BibRef

Cao, J.M.[Jin-Ming], Leng, H.C.[Han-Chao], Lischinski, D.[Dani], Cohen-Or, D.[Danny], Tu, C.H.[Chang-He], Li, Y.Y.[Yang-Yan],
ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation,
ICCV21(7068-7077)
IEEE DOI 2203
Geometry, Point cloud compression, Image segmentation, Convolution, Shape, Semantics, Segmentation, grouping and shape, Scene analysis and understanding BibRef

Jiang, H.L.[Hua-Lie], Ding, L.Y.[Lai-Yan], Hu, J.J.[Jun-Jie], Huang, R.[Rui],
PLNet: Plane and Line Priors for Unsupervised Indoor Depth Estimation,
3DV21(741-750)
IEEE DOI 2201
Point cloud compression, Geometry, Codes, Estimation, Reliability, Unsupervised learning, Depth Estimation, Indoor Scene, Unsupervised Learning BibRef

Zavar, H., Arefi, H., Malihi, S., Maboudi, M.,
Topology-Aware 3D Modelling of Indoor Spaces from Point Clouds,
ISPRS21(B4-2021: 267-274).
DOI Link 2201
BibRef

Wahbeh, W.,
Parametric Modelling Approach to Reconstructing Architectural Indoor Spaces From Point Clouds,
ISPRS21(B4-2021: 251-257).
DOI Link 2201
BibRef

Claridades, A.R.C., Kim, M., Park, S., Lee, J.,
Towards Representing Transitional Spaces: Developmental Direction for IndoorGML Anchor Node,
GeoInfo21(11-16).
DOI Link 2201
BibRef

Gopinathan, M.[Muraleekrishna], Truong, G.[Giang], Abu-Khalaf, J.[Jumana],
Indoor Semantic Scene Understanding Using 2D-3D Fusion,
DICTA21(1-8)
IEEE DOI 2201
Performance evaluation, Image segmentation, Solid modeling, Navigation, Semantics, Pipelines, Scene Understanding, 3D Object Detection BibRef

Sun, C.[Cheng], Hsiao, C.W.[Chi-Wei], Wang, N.H.[Ning-Hsu], Sun, M.[Min], Chen, H.T.[Hwann-Tzong],
Indoor Panorama Planar 3D Reconstruction via Divide and Conquer,
CVPR21(11333-11342)
IEEE DOI 2111
Image segmentation, Estimation, Benchmark testing, Reconstruction algorithms, Cameras, Pattern recognition BibRef

Li, Z.Q.[Zheng-Qin], Yu, T.W.[Ting-Wei], Sang, S.[Shen], Wang, S.[Sarah], Song, M.[Meng], Liu, Y.H.[Yu-Han], Yeh, Y.Y.[Yu-Ying], Zhu, R.[Rui], Gundavarapu, N.[Nitesh], Shi, J.[Jia], Bi, S.[Sai], Yu, H.X.[Hong-Xing], Xu, Z.X.[Ze-Xiang], Sunkavalli, K.[Kalyan], Hašan, M.[Miloš], Ramamoorthi, R.[Ravi], Chandraker, M.[Manmohan],
OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets,
CVPR21(7186-7195)
IEEE DOI 2111
Geometry, Image segmentation, Shape, Semantics, Layout, Lighting, Tools BibRef

Rao, S.[Shivansh], Kumar, V.[Vikas], Kifer, D.[Daniel], Giles, C.L.[C. Lee], Mali, A.[Ankur],
OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas,
OmniCV21(3701-3710)
IEEE DOI 2109
Convolutional codes, Layout, Benchmark testing, Distortion, Predistortion, Pattern recognition BibRef

Gkitsas, V.[Vasileios], Sterzentsenko, V.[Vladimiros], Zioulis, N.[Nikolaos], Albanis, G.[Georgios], Zarpalas, D.[Dimitrios],
PanoDR: Spherical Panorama Diminished Reality for Indoor Scenes,
OmniCV21(3711-3721)
IEEE DOI 2109
Measurement, Image segmentation, Predictive models, Planning, Pattern recognition BibRef

Albanis, G.[Georgios], Zioulis, N.[Nikolaos], Piniotis, G., Soile, S., Bourexis, F., Tsakiri, M., Ioannidis, C.C.,
Experimental Assessment of 3d Narrow Space Mapping Technologies,
ISPRS20(B2:149-156).
DOI Link 2012
BibRef

Diakité, A.A., Zlatanova, S., Alattas, A.F.M., Li, K.J.,
Towards IndoorGML 2.0: Updates and Case Study Illustrations,
ISPRS20(B4:337-344).
DOI Link 2012
BibRef

Poux, F., Ponciano, J.J.,
Self-learning Ontology for Instance Segmentation of 3d Indoor Point Cloud,
ISPRS20(B2:309-316).
DOI Link 2012
BibRef

Mascitelli, A., Ravanelli, M., Mattoccia, S., Berardocco, C., Mazzoni, A.,
A Complete Fos Approach for Indoor Crowdsourced Mapping: Case Study On Sapienza University of Rome Faculties,
ISPRS20(B4:361-365).
DOI Link 2012
BibRef

Gülch, E., Obrock, L.,
Automated Semantic Modelling of Building Interiors From Images And Derived Point Clouds Based on Deep Learning Methods,
ISPRS20(B2:421-426).
DOI Link 2012
BibRef

Wu, T., Vallet, B., Demonceaux, C., Liu, J.,
Moving Objects Aware Sensor Mesh Fusion for Indoor Reconstruction From A Couple of 2d Lidar Scans,
ISPRS20(B2:507-514).
DOI Link 2012
BibRef

Lovas, T., Hadzijanisz, K., Papp, V., Somogyi, A.J.,
Indoor Building Survey Assessment,
ISPRS20(B1:251-257).
DOI Link 2012
BibRef

Poux, F., Mattes, C., Kobbelt, L.,
Unsupervised Segmentation of Indoor 3d Point Cloud: Application To Object-based Classification,
GeoInfo20(111-118).
DOI Link 2012
BibRef

Salgues, H., Macher, H., Landes, T.,
Evaluation of Mobile Mapping Systems for Indoor Surveys,
GeoInfo20(119-125).
DOI Link 2012
BibRef

Sarmiento, A., Diakité, A.A.,
Integration of IOT Sensors to 3d Indoor Models with IndoorGML,
GeoInfo20(135-142).
DOI Link 2012
BibRef

Khoshelham, K., Tran, H., Acharya, D., Vilariño, L.D.[L. Díaz], Kang, Z., Dalyot, S.,
The ISPRS Benchmark on Indoor Modelling - Preliminary Results,
ISPRS20(B5:207-211).
DOI Link 2012
BibRef

Yu, Z.[Zehao], Jin, L.[Lei], Gao, S.H.[Sheng-Hua],
P2 Net: Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation,
ECCV20(XXIV:206-222).
Springer DOI 2012
BibRef

Jiang, Z., Liu, B., Schulter, S., Wang, Z., Chandraker, M.,
Peek-a-Boo: Occlusion Reasoning in Indoor Scenes With Plane Representations,
CVPR20(110-118)
IEEE DOI 2008
Cognition, Layout, Training, Semantics, Predictive models, Measurement BibRef

Jin, L., Xu, Y., Zheng, J., Zhang, J., Tang, R., Xu, S., Yu, J., Gao, S.,
Geometric Structure Based and Regularized Depth Estimation From 360 Indoor Imagery,
CVPR20(886-895)
IEEE DOI 2008
Estimation, Convolution, Layout, Programmable logic arrays, Task analysis, Feeds BibRef

Wald, J., Dhamo, H., Navab, N., Tombari, F.,
Learning 3D Semantic Scene Graphs From 3D Indoor Reconstructions,
CVPR20(3960-3969)
IEEE DOI 2008
Semantics, Solid modeling, Task analysis, Image edge detection, Image segmentation BibRef

Xiong, Z., Yuan, Y., Guo, N., Wang, Q.,
Variational Context-Deformable ConvNets for Indoor Scene Parsing,
CVPR20(3991-4001)
IEEE DOI 2008
Convolution, Kernel, Semantics, Image segmentation, Standards BibRef

Liu, K., Shen, Y., Klopp, J., Chen, L.,
What Synthesis Is Missing: Depth Adaptation Integrated With Weak Supervision for Indoor Scene Parsing,
ICCV19(7344-7353)
IEEE DOI 2004
image colour analysis, supervised learning, indoor scene parsing SUN RGB-D dataset, gHeating systems BibRef

Zhou, J., Wang, Y., Qin, K., Zeng, W.,
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments,
ICCV19(8617-8626)
IEEE DOI 2004
cameras, image colour analysis, image segmentation, image sequences, image texture, object detection, Indoor environments BibRef

Sengupta, S., Gu, J., Kim, K., Liu, G., Jacobs, D., Kautz, J.,
Neural Inverse Rendering of an Indoor Scene From a Single Image,
ICCV19(8597-8606)
IEEE DOI 2004
image reconstruction, learning (artificial intelligence), rendering (computer graphics), neural inverse rendering, Face BibRef

Zhou, Y., While, Z., Kalogerakis, E.,
SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation,
ICCV19(7383-7391)
IEEE DOI 2004
graph theory, image representation, learning (artificial intelligence), message passing, Task analysis BibRef

Ritchie, D.[Daniel], Wang, K.[Kai], Lin, Y.A.[Yu-An],
Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Models,
CVPR19(6175-6183).
IEEE DOI 2002
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Kostoeva, R., Upadhyay, R., Sapar, Y., Zakhor, A.,
Indoor 3d Interactive Asset Detection Using a Smartphone,
Indoor3D19(811-817).
DOI Link 1912
IoT sensors, thermostats, fire sprinklers, EXIT signs, fire alarms, smoke detectors, routers etc. BibRef

Ding, Y., Zheng, X., Xiong, H., Zhang, Y.,
Semantic Segmentation of Indoor 3d Point Cloud With Slenet,
Indoor3D19(785-791).
DOI Link 1912
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Khoshelham, K., Tran, H., Acharya, D.,
Indoor Mapping Eyewear: Geometric Evaluation of Spatial Mapping Capability of Hololens,
Indoor3D19(805-810).
DOI Link 1912
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Capocchiano, F., Ravanelli, R.,
An Original Algorithm for BIM Generation From Indoor Survey Point Clouds,
Indoor3D19(769-776).
DOI Link 1912
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Mukhtar, N.F., Azri, S., Ujang, U., Cuétara, M.G., Retortillo, G.M., Mohd Salleh, S.,
3d Model for Indoor Spaces Using Depth Sensor,
GGT19(471-479).
DOI Link 1912
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Hasler, O., Blaser, S., Nebiker, S.,
Implementation and First Evaluation of An Indoor Mapping Application Using Smartphones and AR Frameworks,
LC3D19(135-141).
DOI Link 1912
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Karam, S., Lehtola, V., Vosselman, G.,
Integrating a Low-cost Mems Imu Into a Laser-based Slam for Indoor Mobile Mapping,
LC3D19(149-156).
DOI Link 1912
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León-Vega, H.A., Rodríguez-Laitón, M.I.,
Fisheye Lens Image Capture Analysis for Indoor 3d Reconstruction And Evaluation,
LC3D19(179-186).
DOI Link 1912
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Stojanovic, V., Trapp, M., Richter, R., Döllner, J.,
A Service-oriented Indoor Point Cloud Processing Pipeline,
LC3D19(339-346).
DOI Link 1912
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Hashim, M.N., Hassan, M.I., Abdul Rahman, A.,
Mobile Indoor Laser Scanning for 3d Strata Registration Purposes Based On Indoorgml,
GGT19(241-245).
DOI Link 1912
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Tessema, L.S., Jaeger, R., Stilla, U.,
A Mathematical Sensor Model for Indoor Use of a Multi-beam Rotating 3d Lidar,
PIA19(227-234).
DOI Link 1912
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Wang, C., Dai, Y., El-Sheimy, N., Wen, C., Retscher, G., Kang, Z., Lingua, A.,
Progress On Isprs Benchmark On Multisensory Indoor Mapping And Positioning,
EuroCOW-M3DMaN19(1709-1713).
DOI Link 1912
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Masiero, A., Fissore, F., Antonello, R., Cenedese, A., Vettore, A.,
A Comparison of Uwb and Motion Capture UAV Indoor Positioning,
EuroCOW-M3DMaN19(1695-1699).
DOI Link 1912
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Wu, W., Chen, C., Cong, Y., Dong, Z., Li, J., Li, S., Dai, W., Yang, B.,
Low-cost Wheeled Robot-borne Laser Scanning System for Indoor And Outdoor 3d Mapping Application,
Laser19(1155-1159).
DOI Link 1912
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Eder, M., Moulon, P., Guan, L.,
Pano Popups: Indoor 3D Reconstruction with a Plane-Aware Network,
3DV19(76-84)
IEEE DOI 1911
Estimation, Task analysis, Layout, Network architecture, Cameras, Deep learning, 360 images, 3d reconstruction BibRef

Lafuente-Arroyo, S.[Sergio], Maldonado-Bascón, S.[Saturnino], Gómez-Moreno, H.[Hilario], Alén-Cordero, C.[Cristina],
Segmentation in Corridor Environments: Combining Floor and Ceiling Detection,
IbPRIA19(II:485-496).
Springer DOI 1910
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Coudron, I.[Inge], Puttemans, S.[Steven], Goedemé, T.[Toon],
Polygonal Reconstruction of Building Interiors from Cluttered Pointclouds,
3D-Wild18(I:459-472).
Springer DOI 1905
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Previtali, M., Barazzetti, L., Roncoroni, F.,
Automated Detection and Layout Regularization of Similar Features In Indoor Point Cloud,
3DARCH19(631-638).
DOI Link 1904
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Cantoni, S., Vassena, G.,
Fast Indoor Mapping to Feed an Indoor DB for Building and Facility Management,
3DARCH19(213-217).
DOI Link 1904
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Barazzetti, L., Previtali, M., Roncoroni, F., Valente, R.,
Connecting Inside and Outside Through 360° Imagery for Close-range Photogrammetry,
3DARCH19(87-92).
DOI Link 1904
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Kim, J.S.[Joon-Seok], Li, K.J.[Ki-Joune],
Simplification of geometric objects in an indoor space,
PandRS(147), 2019, pp. 146-162.
Elsevier DOI 1901
Simplification, Level of detail (LoD), Indoor space, 3D model, Prism model BibRef

Fowler, S.[Sam], Kim, H.S.[Han-Sung], Hilton, A.[Adrian],
Human-Centric Scene Understanding from Single View 360 Video,
3DV18(334-342)
IEEE DOI 1812
image colour analysis, image motion analysis, image reconstruction, image representation, image segmentation, human-scene interaction BibRef

Wang, C., Guo, X.,
Plane-Based Optimization of Geometry and Texture for RGB-D Reconstruction of Indoor Scenes,
3DV18(533-541)
IEEE DOI 1812
cameras, geometry, image colour analysis, image reconstruction, image texture, mesh generation, optimisation, texture optimization BibRef

Qi, S., Zhu, Y., Huang, S., Jiang, C., Zhu, S.,
Human-Centric Indoor Scene Synthesis Using Stochastic Grammar,
CVPR18(5899-5908)
IEEE DOI 1812
Grammar, Layout, Probabilistic logic, Monitoring, Task analysis, Stochastic processes BibRef

Chang, M., Guo, F., Ji, R.,
Depth-assisted RefineNet for Indoor Semantic Segmentation,
ICPR18(1845-1850)
IEEE DOI 1812
image colour analysis, image segmentation, indoor environment, depth-assisted RefineNet, indoor semantic segmentation, Image edge detection BibRef

Maset, E., Magri, L., Fusiello, A.,
Improving Automatic Reconstruction of Interior Walls From Point Cloud Data,
Indoor3D19(849-855).
DOI Link 1912
BibRef
Earlier: A2, A3, Only:
Reconstruction of Interior Walls from Point Cloud Data with Min-Hashed J-Linkage,
3DV18(131-139)
IEEE DOI 1812
feature extraction, image matching, image reconstruction, solid modelling, point cloud data, interior environment, scan2bim BibRef

Purkait, P., Bonde, U., Zach, C.,
Weakly Supervised Learning of Indoor Geometry by Dual Warping,
3DV18(738-746)
IEEE DOI 1812
computational geometry, image colour analysis, learning (artificial intelligence), computational costs, dual warping BibRef

Liu, M., Zhang, Y., He, J., Guo, J., Guo, Y.,
Image-Based 3D Model Retrieval for Indoor Scenes by Simulating Scene Context,
ICIP18(3658-3662)
IEEE DOI 1809
Solid modeling, Context modeling, Indexes, Computational modeling, Estimation, 3D model retrieval, cluttered background BibRef

Troisi, S., Baiocchi, V., del Pizzo, S., Giannone, F.,
A Prompt Methodology to Georeference Complex Hypogea Environments,
3DARCH17(639-644).
DOI Link 1805
Model underground facilities. Conventional photogrammetric/Structure from motion software tools. BibRef

Mandelli, A., Fassi, F., Perfetti, L., Polari, C.,
Testing Different Survey Techniques to Model Architectonic Narrow Spaces,
CIPA17(505-511).
DOI Link 1805
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Lee, J.D., Bhang, K.J., Schuhr, W.,
3d Textured Modelling of Both Exterior And Interior of Korean Styled Architectures,
CIPA17(439-442).
DOI Link 1805
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Caroti, G., Piemonte, A., Martínez-Espejo Zaragoza, I., Brambilla, G.,
Indoor Photogrammetry Using UAVs with Protective Structures: Issues And Precision Tests,
Gi4DM18(137-142).
DOI Link 1805
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Jamali, A., Anton, F., Abdul Rahman, A., Mioc, D.,
A Comparison of Artificial Neural Network And Homotopy Continuation In 3d Interior Building Modelling,
GeoInfo17(13-21).
DOI Link 1805
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Yazdanpour, M., Fan, G., Sheng, W.,
Real-time volumetric reconstruction of Manhattan indoor scenes from depth sequences,
VCIP17(1-4)
IEEE DOI 1804
image matching, image reconstruction, image registration, solid modelling, 3D modeling method, LIDAR ground-truth data, Volumetric reconstruction BibRef

McCormac, J., Handa, A., Leutenegger, S., Davison, A.J.,
SceneNet RGB-D: Can 5M Synthetic Images Beat Generic ImageNet Pre-training on Indoor Segmentation?,
ICCV17(2697-2706)
IEEE DOI 1802
cameras, image colour analysis, image segmentation, image sensors, image sequences, Videos BibRef

Lee, S., Park, S.J., Hong, K.S.,
RDFNet: RGB-D Multi-level Residual Feature Fusion for Indoor Semantic Segmentation,
ICCV17(4990-4999)
IEEE DOI 1802
feature extraction, image classification, image colour analysis, image fusion, image segmentation, Semantics BibRef

Izadinia, H.[Hamid], Shan, Q.[Qi], Seitz, S.M.[Steven M.],
IM2CAD,
CVPR17(2422-2431)
IEEE DOI 1711
Single photo of room and database of furniture models, reconstruct the scene. Computational modeling, Databases, Estimation, Image reconstruction, Solid modeling, BibRef