12.1.4.8 Fusion, Range or Depth and Intensity or Color Data

Chapter Contents (Back)
Fusion. Sensor Fusion. Range. LiDAR. Point Clouds. Depth.
See also RGB-D Laser Scanner Calibration, Color and LIDAR.
See also Image to 3-D Surface Matching, 2-D to 3-D Matching, 2-D to 3-D Registration.

Morgenthaler, D.G., Hennessy, S.J., DeMenthon, D.F.,
Range-Video Fusion and Comparison of Inverse Perspective Algorithms in Static Images,
SMC(20), 1990, pp. 1301-1312. BibRef 9000

Chu, C.C., and Aggarwal, J.K.,
Image Interpretation Using Multiple Sensing Modalities,
PAMI(14), No. 8, August 1992, pp. 840-847.
IEEE DOI BibRef 9208
Earlier:
Multi-Sensor Image Interpretation Using Laser Radar and Thermal Images,
CAIA91(24-28). Combine range, intensity and velocity from ladar with thermal. BibRef

Chu, C.C.[Chen-Chau], Nandhakumar, N., Aggarwal, J.K.,
Image Segmentation Using Laser Radar Data,
PR(23), No. 6, 1990, pp. 569-581.
Elsevier DOI Ladar images, indoor scenes.
See also Pyramid-Based Image Segmentation Using Multisensory Data. BibRef 9000

Chu, C., and Aggarwal, J.K.,
Interpretation of Laser Radar Images by a Knowledge-Based System,
MVA(4), No. 3, August 1991, pp. xx-yy. See above. BibRef 9108

Zhang, G.H., and Wallace, A.M.,
Physical Modeling and Combination of Range and Intensity Edge Data,
CVGIP(58), No. 2, September 1993, pp. 191-220.
DOI Link BibRef 9309
Earlier:
Edge Classification and Depth Reconstruction by Fusion of Range and Intensity Edge Data,
ECCV92(744-748).
Springer DOI BibRef
Earlier:
Edge Labelling by Fusion of Intensity and Range Data,
BMVC91(xx-yy).
PDF File. 9109
BibRef

Zhang, G.H., and Wallace, A.M.,
Extending Semantic Edge Labelling,
BMVC95(xx-yy).
PDF File. 9509
BibRef

Davis, I.L., Stentz, A.,
Sensor Fusion for Autonomous Navigation Using Neural Networks,
NAVLAB96(Chapter 8). BibRef 9600

Nadabar, S.G.[Sateesha G.], Jain, A.K.[Anil K.],
Fusion of range and intensity images on a connection machine (CM-2),
PR(28), No. 1, January 1995, pp. 11-26.
Elsevier DOI 0401
Bayesian framework. BibRef

Lee, G.C.[Greg Chungmou], Stockman, G.[George],
Detection of Object Wings in Fused Range and Intensity Imagery,
PR(31), No. 2, February 1998, pp. 137-158.
Elsevier DOI 9802
primitives in scenes, objects are piecewise quadric. BibRef

Chang, I.S.[In Su], Park, R.H.[Rae-Hong],
Segmentation based on fusion of range and intensity images using robust trimmed methods,
PR(34), No. 10, October 2001, pp. 1951-1962.
Elsevier DOI 0108
Segmentation from fusion of range and intensity.
See also Range image reconstruction based on robust multiresolution estimation of surface parameters. BibRef

Baltzakis, H.G.[Haris G.], Argyros, A.A.[Antonis A.], Trahanias, P.E.[Panos E.],
Fusion of laser and visual data for robot motion planning and collision avoidance,
MVA(15), No. 2, December 2003, pp. 92-100.
Springer DOI 0401
BibRef
Earlier:
Fusion of range and visual data for the extraction of scene structure information,
ICPR02(IV: 7-11).
IEEE DOI 0211
BibRef

Town, C.[Christopher],
Multi-sensory and Multi-modal Fusion for Sentient Computing,
IJCV(71), No. 2, February 2007, pp. 235-253.
Springer DOI 0609
BibRef
Earlier:
Fusion of Visual and Ultrasonic Information for Environmental Modelling,
OTCBVS04(124).
IEEE DOI 0502
Calibrated cameras. SPIRIT system. BibRef

Wendt, A.[Axel],
A concept for feature based data registration by simultaneous consideration of laser scanner data and photogrammetric images,
PandRS(62), No. 2, June 2007, pp. 122-134.
Elsevier DOI 0709
Vision sciences; Photogrammetry; Terrestrial laser scanning; Hybrid sensor; Feature extraction; Registration; Automation BibRef

Wendt, A., Heipke, C.,
Simultaneous orientation of brightness, range and intensity images,
IEVM06(xx-yy).
PDF File. 0609
BibRef

Waske, B., van der Linden, S.,
Classifying Multilevel Imagery From SAR and Optical Sensors by Decision Fusion,
GeoRS(46), No. 5, May 2008, pp. 1457-1466.
IEEE DOI 0804
BibRef

Bannai, N.[Nobuyuki], Fisher, R.B.[Robert B.], Agathos, A.[Alexander],
Multiple color texture map fusion for 3D models,
PRL(28), No. 6, 15 April 2007, pp. 748-758.
Elsevier DOI 0703
BibRef
Earlier: A1, A3, A2:
Fusing multiple color images for texturing models,
3DPVT04(558-565).
IEEE DOI 0412
BibRef
Earlier: A3, A2, Only:
Colour texture fusion of multiple range images,
3DIM03(139-146).
IEEE DOI 0311
Virtual models; Color consistency; Texture mapping; Color matching BibRef

Suri, S., Reinartz, P.,
Mutual-Information-Based Registration of TerraSAR-X and Ikonos Imagery in Urban Areas,
GeoRS(48), No. 2, February 2010, pp. 939-949.
IEEE DOI 1002
BibRef

Suri, S., Türmer, S., Reinartz, P., Stilla, U.,
Registration of High Resolution SAR and Optical Satellite Imagery in Urban Areas,
HighRes09(xx-yy).
PDF File. 0906
BibRef

Gurram, P., Saber, E., Rhody, H.,
A Segment-Based Mesh Design for Building Parallel-Perspective Stereo Mosaics,
GeoRS(48), No. 3, March 2010, pp. 1256-1269.
IEEE DOI 1003
BibRef

Gurram, P., Rhody, H., Saber, E., Sahin, F.,
Automated 3D object identification using Bayesian networks,
AIPR09(1-8).
IEEE DOI 0910
BibRef

Gurram, P., Rhody, H., Kerekes, J., Lach, S., Saber, E.,
3D Scene Reconstruction through a Fusion of Passive Video and Lidar Imagery,
AIPR07(133-138).
IEEE DOI 0710
BibRef

Herrera, D.C.[Daniel C.], Kannala, J.H.[Ju-Ho], Heikkilä, J.[Janne],
Joint Depth and Color Camera Calibration with Distortion Correction,
PAMI(34), No. 10, October 2012, pp. 2058-2064.
IEEE DOI 1208
BibRef
Earlier:
Accurate and Practical Calibration of a Depth and Color Camera Pair,
CAIP11(II: 437-445).
Springer DOI 1109
Simultaneously calibrates two color cameras, a depth camera, and the relative pose between them. BibRef

Herrera, C.D., Kannala, J.H., Sturm, P.F., Heikkila, J.,
A Learned Joint Depth and Intensity Prior Using Markov Random Fields,
3DV13(17-24)
IEEE DOI 1311
Markov processes BibRef

Braun, A.C.[Andreas C.], Weidner, U.[Uwe], Jutzi, B.[Boris], Hinz, S.[Stefan],
Kernel Composition with the one-against-one Cascade for Integrating External Knowledge into SVM Classification,
PFG(2012), No. 4, 2012, pp. 371-384.
WWW Link. 1211
BibRef
Earlier:
Integrating external knowledge into SVM classification: Fusing hyperspectral and laserscanning data by kernel composition.,
HighRes11(xx-yy).
PDF File. 1106
BibRef

Braun, A.C.[Andreas Christian], Weidner, U.[Uwe], Hinz, S.[Stefan],
Support Vector Machines for Vegetation Classification A Revision,
PFG(2010), No. 4, 2010, pp. 273-281.
WWW Link. 1211
BibRef

Ju, H.[Hui], Toth, C.K.[Charles K.], Grejner-Brzezinska, D.A.[Dorota A.],
A New Approach to Robust LiDAR/Optical Imagery Registration,
PFG(2012), No. 5, 2012, pp. 523-534.
WWW Link. 1211
BibRef
And: A2, A1, A3:
Matching between Different Image Domains,
PIA11(37-47).
Springer DOI 1110
BibRef

Alismail, H.[Hatem], Baker, L.D.[L. Douglas], Browning, B.[Brett],
Automatic Calibration of a Range Sensor and Camera System,
3DIMPVT12(286-292).
IEEE DOI 1212
BibRef

Shah, P.[Parul], Merchant, S.N.[Shabbir N.], Desai, U.B.[Uday B.],
Multifocus and multispectral image fusion based on pixel significance using multiresolution decomposition,
SIViP(7), No. 1, January 2013, pp. 95-109.
WWW Link. 1301
BibRef

Shah, P.[Parul], Srikanth, T.V., Merchant, S.N.[Shabbir N.], Desai, U.B.[Uday B.],
Multimodal image/video fusion rule using generalized pixel significance based on statistical properties of the neighborhood,
SIViP(8), No. 4, May 2014, pp. 723-738.
Springer DOI 1404
BibRef

Han, J., Shao, L., Xu, D., Shotton, J.,
Enhanced Computer Vision With Microsoft Kinect Sensor: A Review,
Cyber(43), No. 5, 2013, pp. 1318-1334.
IEEE DOI 1309
omputer vision; Kinect sensor; depth image; information fusion BibRef

Camplani, M., Mantecon, T., Salgado, L.,
Depth-Color Fusion Strategy for 3-D Scene Modeling With Kinect,
Cyber(43), No. 6, 2013, pp. 1560-1571.
IEEE DOI 1312
adaptive filters BibRef

Flener, C.[Claude], Vaaja, M.[Matti], Jaakkola, A.[Anttoni], Krooks, A.[Anssi], Kaartinen, H.[Harri], Kukko, A.[Antero], Kasvi, E.[Elina], Hyyppä, H.[Hannu], Hyyppä, J.[Juha], Alho, P.[Petteri],
Seamless Mapping of River Channels at High Resolution Using Mobile LiDAR and UAV-Photography,
RS(5), No. 12, 2013, pp. 6382-6407.
DOI Link 1402
BibRef

Vaaja, M.[Matti], Kurkela, M.[Matti], Hyyppä, H.[Hannu], Alho, P.[Petteri], Hyyppä, J.[Juha], Kukko, A.[Antero], Kaartinen, H.[Harri], Kasvi, E.[Elina], Kaasalainen, S.[Sanna], Rönnholm, P.[Petri],
Fusion of Mobile Laser Scanning and Panoramic Images for Studying River Environment Topography And Changes,
Laser11(xx-yy).
DOI Link 1109
BibRef

Zhao, G.Q.[Gang-Qiang], Xiao, X.H.[Xu-Hong], Yuan, J.S.[Jun-Song], Ng, G.W.[Gee Wah],
Fusion of 3D-LIDAR and camera data for scene parsing,
JVCIR(25), No. 1, 2014, pp. 165-183.
Elsevier DOI 1502
Scene parsing BibRef

Gerke, M.[Markus], Xiao, J.[Jing],
Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification,
PandRS(87), No. 1, 2014, pp. 78-92.
Elsevier DOI 1402
Visibility BibRef

Gerke, M., Nex, F., Jende, P.,
Co-Registration of Terrestrial and UAV-Based Images: Experimental Results,
EuroCOW16(xx-yy).
DOI Link 1605
BibRef

Mikhelson, I.V.[Ilya V.], Lee, P.G.[Philip G.], Sahakian, A.V.[Alan V.], Wu, Y.[Ying], Katsaggelos, A.K.[Aggelos K.],
Automatic, fast, online calibration between depth and color cameras,
JVCIR(25), No. 1, 2014, pp. 218-226.
Elsevier DOI 1502
Calibration BibRef

Parmehr, E.G.[Ebadat G.], Fraser, C.S.[Clive S.], Zhang, C.S.[Chun-Sun], Leach, J.[Joseph],
Automatic registration of optical imagery with 3D LiDAR data using statistical similarity,
PandRS(88), No. 1, 2014, pp. 28-40.
Elsevier DOI 1402
BibRef
Earlier:
An effective histogram binning for mutual information based registration of optical imagery and 3D LiDAR data,
ICIP13(1286-1290)
IEEE DOI 1402
BibRef
Earlier:
Automatic Registration of Aerial Images with 3D LiDAR Data Using a Hybrid Intensity-Based Method,
DICTA12(1-7).
IEEE DOI 1303
Biomedical imaging Registration BibRef

Parmehr, E.G.[Ebadat G.], Fraser, C.S.[Clive S.], Zhang, C.S.[Chun-Sun],
Automatic Parameter Selection for Intensity-Based Registration of Imagery to LiDAR Data,
GeoRS(54), No. 12, December 2016, pp. 7032-7043.
IEEE DOI 1612
BibRef
Earlier: A1, A3, A2:
Automatic Registration of Multi-source Data Using Mutual Information,
AnnalsPRS(I-7), No. 2012, pp. 303-308.
DOI Link 1209
geographic information systems BibRef

Lee, J.[Juheon], Cai, X.H.[Xiao-Hao], Schonlieb, C.B., Coomes, D.A.,
Nonparametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Wooded Landscapes,
GeoRS(53), No. 11, November 2015, pp. 6073-6084.
IEEE DOI 1509
geophysical image processing BibRef

Mutto, C.D.[Carlo Dal], Zanuttigh, P.[Pietro], Cortelazzo, G.M.[Guido Maria],
Probabilistic ToF and Stereo Data Fusion Based on Mixed Pixels Measurement Models,
PAMI(37), No. 11, November 2015, pp. 2260-2272.
IEEE DOI 1511
BibRef
Earlier:
A Probabilistic Approach to ToF and Stereo Data Fusion,
3DPVT10(xx-yy).
WWW Link. 1005
image fusion BibRef

Marin, G.[Giulio], Zanuttigh, P.[Pietro], Mattoccia, S.[Stefano],
Reliable Fusion of ToF and Stereo Depth Driven by Confidence Measures,
ECCV16(VII: 386-401).
Springer DOI 1611
BibRef

Mutto, C.D.[Carlo Dal], Zanuttigh, P.[Pietro], Mattoccia, S.[Stefano], Cortelazzo, G.M.[Guido Maria],
Locally Consistent ToF and Stereo Data Fusion,
CDC4CV12(I: 598-607).
Springer DOI 1210
BibRef

Kwak, K.[Kiho], Kim, J.S.[Jun-Sik], Huberr, D.F.[Daniel F.], Kanade, T.[Takeo],
Online Approximate Model Representation Based on Scale-Normalized and Fronto-Parallel Appearance,
IJCV(117), No. 1, March 2016, pp. 48-69.
Springer DOI 1604
BibRef

Brell, M., Rogass, C., Segl, K., Bookhagen, B., Guanter, L.,
Improving Sensor Fusion: A Parametric Method for the Geometric Coalignment of Airborne Hyperspectral and Lidar Data,
GeoRS(54), No. 6, June 2016, pp. 3460-3474.
IEEE DOI 1606
geophysical image processing BibRef

Safdarinezhad, A.[Alireza], Mokhtarzade, M.[Mehdi], Zoej, M.J.V.[Mohammad Javad Valadan],
Shadow-Based Hierarchical Matching for the Automatic Registration of Airborne LiDAR Data and Space Imagery,
RS(8), No. 6, 2016, pp. 466.
DOI Link 1608
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Brell, M., Segl, K., Guanter, L., Bookhagen, B.,
Hyperspectral and Lidar Intensity Data Fusion: A Framework for the Rigorous Correction of Illumination, Anisotropic Effects, and Cross Calibration,
GeoRS(55), No. 5, May 2017, pp. 2799-2810.
IEEE DOI 1705
geophysical image processing, hyperspectral imaging, image classification, image fusion, land use, optical radar, remote sensing by laser beam, vegetation, active sensor system, airborne lidar scanner, anisotropy effect, geometric accuracy, hyperspectral data, BibRef

Zhang, R.C.[Rong-Chun], Li, H.[Hao], Liu, L.[Lanfa], Wu, M.F.[Ming-Fei],
A G-Super4PCS Registration Method for Photogrammetric and TLS Data in Geology,
IJGI(6), No. 5, 2017, pp. xx-yy.
DOI Link 1706
TLS: Terrestrial Laser Scanner BibRef

Kandare, K.[Kaja], Dalponte, M.[Michele], Ørka, H.O.[Hans Ole], Frizzera, L.[Lorenzo], Næsset, E.[Erik],
Prediction of Species-Specific Volume Using Different Inventory Approaches by Fusing Airborne Laser Scanning and Hyperspectral Data,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Rasti, B.[Behnood], Ghamisi, P.[Pedram], Plaza, J., Plaza, A.,
Fusion of Hyperspectral and LiDAR Data Using Sparse and Low-Rank Component Analysis,
GeoRS(55), No. 11, November 2017, pp. 6354-6365.
IEEE DOI 1711
Data mining, Feature extraction, Gray-scale, Hyperspectral imaging, Laser radar, Extinction profiles (EPs), hyperspectral, light detection and ranging (LiDAR), sparse, and, low-rank, component, analysis, (SLRCA) BibRef

Rasti, B.[Behnood], Ghamisi, P.[Pedram], Ulfarsson, M.O.[Magnus O.],
Hyperspectral Feature Extraction Using Sparse and Smooth Low-Rank Analysis,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Rasti, B., Ulfarsson, M.O., Sveinsson, J.R.,
Hyperspectral Feature Extraction Using Total Variation Component Analysis,
GeoRS(54), No. 12, December 2016, pp. 6976-6985.
IEEE DOI 1612
feature extraction BibRef

Rasti, B., Ghamisi, P., Gloaguen, R.,
Hyperspectral and LiDAR Fusion Using Extinction Profiles and Total Variation Component Analysis,
GeoRS(55), No. 7, July 2017, pp. 3997-4007.
IEEE DOI 1706
Data mining, Feature extraction, Hyperspectral imaging, Laser radar, Support vector machines, Extinction profiles (EPs), feature fusion, orthogonal total variation component analysis (OTVCA), random forest (RF), support, vector, machines, (SVMs) BibRef

Li, J.P.[Jian-Ping], Yang, B.S.[Bi-Sheng], Chen, C.[Chi], Huang, R.G.[Rong-Gang], Dong, Z.[Zhen], Xiao, W.[Wen],
Automatic registration of panoramic image sequence and mobile laser scanning data using semantic features,
PandRS(136), 2018, pp. 41-57.
Elsevier DOI 1802
Panoramic image sequence, Mobile laser scanning data, Semantic features, Registration BibRef

Yamaguchi, M.[Masahiro], Truong, T.P.[Trong Phuc], Mori, S.[Shohei], Nozick, V.[Vincent], Saito, H.[Hideo], Yachida, S.[Shoji], Sato, H.[Hideaki],
Superimposing Thermal-Infrared Data on 3D Structure Reconstructed by RGB Visual Odometry,
IEICE(E101-D), No. 5, May 2018, pp. 1296-1307.
WWW Link. 1805
BibRef

Choi, K.H.[Kang Hyeok], Kim, C.J.[Chang-Jae], Kim, Y.G.[Yon-Gil],
Comprehensive Analysis of System Calibration between Optical Camera and Range Finder,
IJGI(7), No. 5, 2018, pp. xx-yy.
DOI Link 1806
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Zhang, R.[Rui], Li, G.Y.[Guang-Yun], Li, M.L.[Ming-Lei], Wang, L.[Li],
Fusion of images and point clouds for the semantic segmentation of large-scale 3D scenes based on deep learning,
PandRS(143), 2018, pp. 85-96.
Elsevier DOI 1808
3D scene segmentation, 2D image, 3D point cloud, Large-scale, High-resolution BibRef

Xiang, X.Y.[Xue-Yong], Zong, W.P.[Wen-Peng], Li, G.Y.[Guang-Yun],
Learnable Upsampling-Based Point Cloud Semantic Segmentation,
ICIVC22(340-347)
IEEE DOI 2301
Point cloud compression, Image segmentation, Interpolation, Costs, Correlation, Semantics, point cloud, semantic segmentation, upsamping BibRef

Li, H.[Hao], Ghamisi, P.[Pedram], Soergel, U.[Uwe], Zhu, X.X.[Xiao Xiang],
Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
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Polewski, P.[Przemyslaw], Yao, W.[Wei], Cao, L.[Lin], Gao, S.[Sha],
Marker-free coregistration of UAV and backpack LiDAR point clouds in forested areas,
PandRS(147), 2019, pp. 307-318.
Elsevier DOI 1901
Coregistration, Unmanned aerial vehicle, Backpack laser scanning, Graph matching, Precision forestry BibRef

Brell, M.[Maximilian], Segl, K.[Karl], Guanter, L.[Luis], Bookhagen, B.[Bodo],
3D hyperspectral point cloud generation: Fusing airborne laser scanning and hyperspectral imaging sensors for improved object-based information extraction,
PandRS(149), 2019, pp. 200-214.
Elsevier DOI 1903
Lidar, Multispectral point cloud, Laser return intensity, Unmixing, Sharpening, Imaging spectroscopy, In-flight, Semantic labeling BibRef

Li, Y.S.[Yun-Song], Ge, C.[Chiru], Sun, W.W.[Wei-Wei], Peng, J.T.[Jiang-Tao], Du, Q.[Qian], Wang, K.[Keyan],
Hyperspectral and LiDAR Data Fusion Classification Using Superpixel Segmentation-Based Local Pixel Neighborhood Preserving Embedding,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
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Slawik, L.[Lukasz], Niedzielko, J.[Jan], Kania, A.[Adam], Piórkowski, H.[Hubert], Kopec, D.[Dominik],
Multiple Flights or Single Flight Instrument Fusion of Hyperspectral and ALS Data? A Comparison of their Performance for Vegetation Mapping,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
Airborne Laser System. BibRef

Zhou, K.Q.[Ke-Qi], Ming, D.P.[Dong-Ping], Lv, X.W.[Xian-Wei], Fang, J.[Ju], Wang, M.[Min],
CNN-Based Land Cover Classification Combining Stratified Segmentation and Fusion of Point Cloud and Very High-Spatial Resolution Remote Sensing Image Data,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909
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Xue, Z.H.[Zhao-Hui], Yang, S.[Sirui], Zhang, H.Y.[Hong-Yan], Du, P.J.[Pei-Jun],
Coupled Higher-Order Tensor Factorization for Hyperspectral and LiDAR Data Fusion and Classification,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909
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Zhang, W.Y.[Wan-Yi], Fu, X.H.[Xiu-Hua], Wang, C.Y.[Chun-Yang],
Image quality optimization towards lidar registration based on iterative termination,
JVCIR(64), 2019, pp. 102634.
Elsevier DOI 1911
Laser radar, Registration image, Quality optimization, Image processing BibRef

Bybee, T.C., Budge, S.E.,
Method for 3-D Scene Reconstruction Using Fused LiDAR and Imagery From a Texel Camera,
GeoRS(57), No. 11, November 2019, pp. 8879-8889.
IEEE DOI 1911
Laser radar, Cameras, Image reconstruction, Aircraft navigation, Aircraft, Surface reconstruction, Bundle adjustment, remote sensing BibRef

Gong, Z.[Zheng], Lin, H.J.[Hao-Jia], Zhang, D.D.[De-Dong], Luo, Z.P.[Zhi-Peng], Zelek, J.[John], Chen, Y.P.[Yi-Ping], Nurunnabi, A.[Abdul], Wang, C.[Cheng], Li, J.[Jonathan],
A Frustum-based probabilistic framework for 3D object detection by fusion of LiDAR and camera data,
PandRS(159), 2020, pp. 90-100.
Elsevier DOI 1912
3D object detection, CNN, Deep learning, LiDAR point clouds, MLS, SLAM BibRef

Park, K.[Kihong], Kim, S.[Seungryong], Sohn, K.H.[Kwang-Hoon],
High-Precision Depth Estimation Using Uncalibrated LiDAR and Stereo Fusion,
ITS(21), No. 1, January 2020, pp. 321-335.
IEEE DOI 2001
Laser radar, Calibration, Robot sensing systems, Cameras, Estimation, Interpolation, 3D reconstruction BibRef

Liu, J., Zhang, L., Wang, Z., Wang, R.,
A New Fusion Algorithm for Depth Images Based on Virtual Views,
GeoRS(58), No. 2, February 2020, pp. 1171-1181.
IEEE DOI 2001
Image fusion, Optical imaging, Cameras, Surface reconstruction, Fuses, Redundancy, Depth image, virtual view BibRef

Hang, R., Li, Z., Ghamisi, P., Hong, D., Xia, G., Liu, Q.,
Classification of Hyperspectral and LiDAR Data Using Coupled CNNs,
GeoRS(58), No. 7, July 2020, pp. 4939-4950.
IEEE DOI 2006
Hyperspectral imaging, Laser radar, Feature extraction, Fuses, Data models, Convolutional neural networks (CNNs), parameter sharing BibRef

Gong, B.[Biao], Yan, C.G.[Cheng-Gang], Bai, J.J.[Jun-Jie], Zou, C.Q.[Chang-Qing], Gao, Y.[Yue],
Hamming Embedding Sensitivity Guided Fusion Network for 3D Shape Representation,
IP(29), 2020, pp. 8381-8390.
IEEE DOI 2008
Feature extraction, Shape, Data mining, Task analysis, Sensitivity, Convolution, 3D Multimodal fusion, mesh, hamming space BibRef

Zhao, X., Tao, R., Li, W., Li, H.C., Du, Q., Liao, W., Philips, W.,
Joint Classification of Hyperspectral and LiDAR Data Using Hierarchical Random Walk and Deep CNN Architecture,
GeoRS(58), No. 10, October 2020, pp. 7355-7370.
IEEE DOI 2009
Feature extraction, Laser radar, Hyperspectral imaging, Convolution, Probability distribution, hierarchical random walk BibRef

Gao, X., Shen, S., Zhu, L., Shi, T., Wang, Z., Hu, Z.,
Complete Scene Reconstruction by Merging Images and Laser Scans,
CirSysVideo(30), No. 10, October 2020, pp. 3688-3701.
IEEE DOI 2010
Image reconstruction, Pipelines, Laser modes, Merging, Planning, image synthesis and matching BibRef

Wang, X.Y.[Xuan-Yin], Lin, T.P.[Tian-Pei], Jiang, X.S.[Xue-Song], Xiang, K.[Ke], Pan, F.[Feng],
Reliable fusion of ToF and stereo data based on joint depth filter,
JVCIR(74), 2021, pp. 103006.
Elsevier DOI 2101
ToF, Stereo vision, Data fusion, 3D block matching, Seed-growing BibRef

Jia, S.[Sen], Zhan, Z.W.[Zhang-Wei], Zhang, M.[Meng], Xu, M.[Meng], Huang, Q.[Qiang], Zhou, J.[Jun], Jia, X.P.[Xiu-Ping],
Multiple Feature-Based Superpixel-Level Decision Fusion for Hyperspectral and LiDAR Data Classification,
GeoRS(59), No. 2, February 2021, pp. 1437-1452.
IEEE DOI 2101
Laser radar, Feature extraction, Hyperspectral imaging, Sensors, Data mining, Feature extraction, feature fusion, superpixel segmentation BibRef

Jia, S.[Sen], Zhang, M.[Meng], Xian, J.J.[Jun-Jian], Zhuang, J.Y.[Jia-Yue], Huang, Q.[Qiang],
Superpixel-Based Feature Extraction and Fusion Method for Hyperspectral and LiDAR Classification,
ICPR18(764-769)
IEEE DOI 1812
Feature extraction, Hyperspectral imaging, Laser radar, Wavelet domain, Entropy, Image segmentation BibRef

Megahed, Y.[Yasmine], Shaker, A.[Ahmed], Yan, W.Y.[Wai Yeung],
Fusion of Airborne LiDAR Point Clouds and Aerial Images for Heterogeneous Land-Use Urban Mapping,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Chen, B., Shi, S., Sun, J., Chen, B., Guo, K., Du, L., Yang, J., Xu, Q., Song, S., Gong, W.,
Using HSI Color Space to Improve the Multispectral Lidar Classification Error Caused by Measurement Geometry,
GeoRS(59), No. 4, April 2021, pp. 3567-3579.
IEEE DOI 2104
Image color analysis, Laser radar, Radiometry, Calibration, Ceramics, Geometry, Imaging, Hue-saturation-intensity (HSI) color space, target classification BibRef

Fekry, R.[Reda], Yao, W.[Wei], Cao, L.[Lin], Shen, X.[Xin],
Marker-Less UAV-LiDAR Strip Alignment in Plantation Forests Based on Topological Persistence Analysis of Clustered Canopy Cover,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Bai, L.[Ling], Li, Y.G.[Yin-Guo], Cen, M.[Ming], Hu, F.C.[Fang-Chao],
3D Instance Segmentation and Object Detection Framework Based on the Fusion of Lidar Remote Sensing and Optical Image Sensing,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Li, Y.[Yong], Luo, Y.Z.[Yin-Zheng], Gu, X.[Xia], Chen, D.[Dong], Gao, F.[Fang], Shuang, F.[Feng],
Point Cloud Classification Algorithm Based on the Fusion of the Local Binary Pattern Features and Structural Features of Voxels,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Zhu, Z.[Zifa], Ma, Y.[Yuebo], Zhao, R.[Rujin], Liu, E.[Enhai], Zeng, S.[Sikang], Yi, J.H.[Jin-Hui], Ding, J.[Jian],
Improve the Estimation of Monocular Vision 6-DOF Pose Based on the Fusion of Camera and Laser Rangefinder,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Fu, H.[Hao], Xue, H.Z.[Han-Zhang], Hu, X.C.[Xiao-Chang], Liu, B.[Bokai],
LiDAR Data Enrichment by Fusing Spatial and Temporal Adjacent Frames,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Zhu, B.[Bai], Ye, Y.X.[Yuan-Xin], Zhou, L.[Liang], Li, Z.L.[Zhi-Lin], Yin, G.F.[Gao-Fei],
Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features,
PandRS(181), 2021, pp. 129-147.
Elsevier DOI 2110
Co-registration, Aerial images, LiDAR, Spatial constraints, Gabor structural features, SDFG BibRef

Zhao, J.H.[Jiang-Hong], Wang, Y.R.[Yin-Rui], Cao, Y.[Yuee], Guo, M.[Ming], Huang, X.F.[Xian-Feng], Zhang, R.J.[Rui-Ju], Dou, X.T.[Xin-Tong], Niu, X.Y.[Xin-Yu], Cui, Y.Y.[Yuan-Yuan], Wang, J.[Jun],
The Fusion Strategy of 2D and 3D Information Based on Deep Learning: A Review,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Yao, C.J.[Chun-Jing], Ma, H.C.[Hong-Chao], Luo, W.J.[Wen-Jun], Ma, H.[Haichi],
A Precisely One-Step Registration Methodology for Optical Imagery and LiDAR Data Using Virtual Point Primitives,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Chen, Y.M.[Yan-Ming], Liu, X.Q.[Xiao-Qiang], Xiao, Y.J.[Yi-Jia], Zhao, Q.Q.[Qi-Qi], Wan, S.[Sida],
Three-Dimensional Urban Land Cover Classification by Prior-Level Fusion of LiDAR Point Cloud and Optical Imagery,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhang, Y.J.[Yong-Jun], Zou, S.Y.[Si-Yuan], Liu, X.[Xinyi], Huang, X.[Xu], Wan, Y.[Yi], Yao, Y.X.[Yong-Xiang],
LiDAR-guided stereo matching with a spatial consistency constraint,
PandRS(183), 2022, pp. 164-177.
Elsevier DOI 2201
LiDAR, Stereo matching, Semi-global matching, AD-Census, Multi-modal data fusion, Spatial consistency constraint BibRef

Cui, Y.D.[Yao-Dong], Chen, R.[Ren], Chu, W.B.[Wen-Bo], Chen, L.[Long], Tian, D.X.[Da-Xin], Li, Y.[Ying], Cao, D.[Dongpu],
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review,
ITS(23), No. 2, February 2022, pp. 722-739.
IEEE DOI 2202
Feature extraction, Deep learning, Laser radar, Convolution, Semantics, Geometry, Camera-LiDAR fusion, sensor fusion, deep learning BibRef

Ling, X.[Xiao], Qin, R.[Rongjun],
A graph-matching approach for cross-view registration of over-view and street-view based point clouds,
PandRS(185), 2022, pp. 2-15.
Elsevier DOI 2202
Cross-view registration, Global optimization, Multi-view satellite image BibRef

Chen, J.[Jiyi], Tang, X.M.[Xin-Ming], Xue, Y.[Yucai], Li, G.Y.[Guo-Yuan], Zhou, X.Q.[Xiao-Qing], Hu, L.[Liuru], Zhang, S.T.[Shuai-Tai],
Registration and Combined Adjustment for the Laser Altimetry Data and High-Resolution Optical Stereo Images of the GF-7 Satellite,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Liu, C.R.[Chang-Ru], Cui, X.[Ximin], Guo, L.[Li], Wu, L.[Ling], Tang, X.M.[Xin-Ming], Liu, S.H.[Shu-Han], Yuan, D.[Debao], Wang, X.[Xia],
Satellite Laser Altimetry Data-Supported High-Accuracy Mapping of GF-7 Stereo Images,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Tang, X.M.[Xin-Ming], Zhou, P.[Ping], Guo, L.[Li], Pan, H.B.[Hong-Bo],
Integrating Stereo Images and Laser Altimetry Points Derived from the Same Satellite for High-Accuracy Stereo Mapping,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Tu, B.[Bing], Zhu, Y.[Yu], Zhou, C.[Chengle], Chen, S.Y.[Si-Yuan], Plaza, A.[Antonio],
Optimized Spatial Gradient Transfer for Hyperspectral-LiDAR Data Classification,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Loghin, A.M.[Ana-Maria], Otepka-Schremmer, J.[Johannes], Ressl, C.[Camillo], Pfeifer, N.[Norbert],
Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Deng, Y.[Yong], Xiao, J.[Jimin], Zhou, S.Z.Y.[Steven Zhi-Ying],
ToF and Stereo Data Fusion Using Dynamic Search Range Stereo Matching,
MultMed(24), 2022, pp. 2739-2751.
IEEE DOI 2206
Estimation, Reliability, Cameras, Data integration, Feature extraction, Task analysis, Probabilistic logic, neural network BibRef

Norton, C.L.[Cynthia L.], Hartfield, K.[Kyle], Collins, C.D.H.[Chandra D. Holifield], van Leeuwen, W.J.D.[Willem J. D.], Metz, L.J.[Loretta J.],
Multi-Temporal LiDAR and Hyperspectral Data Fusion for Classification of Semi-Arid Woody Cover Species,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Xu, X.B.[Xia-Bin], Zhang, L.[Lei], Yang, J.[Jian], Cao, C.F.[Chen-Fei], Wang, W.[Wen], Ran, Y.Y.[Ying-Ying], Tan, Z.Y.[Zhi-Ying], Luo, M.Z.[Min-Zhou],
A Review of Multi-Sensor Fusion SLAM Systems Based on 3D LIDAR,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Berrio, J.S.[Julie Stephany], Shan, M.[Mao], Worrall, S.[Stewart], Nebot, E.[Eduardo],
Camera-LIDAR Integration: Probabilistic Sensor Fusion for Semantic Mapping,
ITS(23), No. 7, July 2022, pp. 7637-7652.
IEEE DOI 2207
Laser radar, Cameras, Uncertainty, Semantics, Probabilistic logic, Sensor fusion, Sensor fusion, heuristic, uncertainty, semantic, mapping BibRef

Zhou, L.[Lin], Geng, J.[Jie], Jiang, W.[Wen],
Joint Classification of Hyperspectral and LiDAR Data Based on Position-Channel Cooperative Attention Network,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Beltrán, J.[Jorge], Guindel, C.[Carlos], de la Escalera, A.[Arturo], García, F.[Fernando],
Automatic Extrinsic Calibration Method for LiDAR and Camera Sensor Setups,
ITS(23), No. 10, October 2022, pp. 17677-17689.
IEEE DOI 2210
Calibration, Laser radar, Robot sensing systems, Performance evaluation, Machine vision, Automatic calibration, stereo cameras BibRef

Peng, Y.[Ying], Qin, Y.[Yechen], Tang, X.L.[Xiao-Lin], Zhang, Z.Q.[Zhi-Qiang], Deng, L.[Lei],
Survey on Image and Point-Cloud Fusion-Based Object Detection in Autonomous Vehicles,
ITS(23), No. 12, December 2022, pp. 22772-22789.
IEEE DOI 2212
Survey, Point Cloud Fusion. Object detection, Feature extraction, Cameras, Autonomous vehicles, Detectors, Laser radar, Deep learning, Autonomous vehicle, point-cloud BibRef

Chen, C.K.[Cheng-Kai], Lan, J.H.[Jin-Hui], Liu, H.T.[Hao-Ting], Chen, S.[Shuai], Wang, X.H.[Xiao-Han],
Automatic Calibration between Multi-Lines LiDAR and Visible Light Camera Based on Edge Refinement and Virtual Mask Matching,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Yan, S.[Shen], Zhang, M.[Maojun], Peng, Y.[Yang], Liu, Y.[Yu], Tan, H.L.[Han-Lin],
AgentI2P: Optimizing Image-to-Point Cloud Registration via Behaviour Cloning and Reinforcement Learning,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zhu, A.[Angfan], Xiao, Y.[Yang], Liu, C.X.[Cheng-Xin], Cao, Z.G.[Zhi-Guo],
Robust LiDAR-Camera Alignment With Modality Adapted Local-to-Global Representation,
CirSysVideo(33), No. 1, January 2023, pp. 59-73.
IEEE DOI 2301
Cameras, Laser radar, Feature extraction, Representation learning, Estimation, Transformers, Point cloud compression, vision transformer BibRef

Zhu, A.[Angfan], Xiao, Y.[Yang], Liu, C.X.[Cheng-Xin], Tan, M.K.[Ming-Kui], Cao, Z.G.[Zhi-Guo],
Lightweight LiDAR-Camera Alignment With Homogeneous Local-Global Aware Representation,
ITS(25), No. 11, November 2024, pp. 15922-15933.
IEEE DOI Code:
WWW Link. 2411
Laser radar, Cameras, Transformers, Convolutional neural networks, Feature extraction, 6-DOF, Representation learning, transformer BibRef

Zhang, M.[Maqun], Gao, F.[Feng], Zhang, T.[Tiange], Gan, Y.[Yanhai], Dong, J.Y.[Jun-Yu], Yu, H.[Hui],
Attention Fusion of Transformer-Based and Scale-Based Method for Hyperspectral and LiDAR Joint Classification,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Zhang, K.P.[Kun-Peng], Liu, Y.H.[Yan-Heng], Mei, F.[Fang], Jin, J.Y.[Jing-Yi], Wang, Y.M.[Yi-Ming],
Boost Correlation Features with 3D-MiIoU-Based Camera-LiDAR Fusion for MODT in Autonomous Driving,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Wu, H.B.[Hai-Bin], Dai, S.Y.[Shi-Yu], Liu, C.Y.[Cheng-Yang], Wang, A.[Aili], Iwahori, Y.[Yuji],
A Novel Dual-Encoder Model for Hyperspectral and LiDAR Joint Classification via Contrastive Learning,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Xu, X.L.[Xin-Li], Dong, S.C.[Shao-Cong], Xu, T.F.[Ting-Fa], Ding, L.[Lihe], Wang, J.[Jie], Jiang, P.[Peng], Song, L.Q.[Li-Qiang], Li, J.A.[Jian-An],
FusionRCNN: LiDAR-Camera Fusion for Two-Stage 3D Object Detection,
RS(15), No. 7, 2023, pp. 1839.
DOI Link 2304
BibRef

Zhang, M.M.[Meng-Meng], Li, W.[Wei], Zhang, Y.X.[Yu-Xiang], Tao, R.[Ran], Du, Q.[Qian],
Hyperspectral and LiDAR Data Classification Based on Structural Optimization Transmission,
Cyber(53), No. 5, May 2023, pp. 3153-3164.
IEEE DOI 2305
Laser radar, Feature extraction, Optimization, Indexes, Hyperspectral imaging, Collaboration, Task analysis, pattern recognition remote sensing BibRef

Xu, J.H.[Jun-Hao], Yao, C.J.[Chun-Jing], Ma, H.C.[Hong-Chao], Qian, C.[Chen], Wang, J.[Jie],
Automatic Point Cloud Colorization of Ground-Based LiDAR Data Using Video Imagery without Position and Orientation System,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Song, H.[Huacui], Yang, Y.[Yuanwei], Gao, X.J.[Xian-Jun], Zhang, M.[Maqun], Li, S.H.[Shao-Hua], Liu, B.[Bo], Wang, Y.J.[Yan-Jun], Kou, Y.[Yuan],
Joint Classification of Hyperspectral and LiDAR Data Using Binary-Tree Transformer Network,
RS(15), No. 11, 2023, pp. 2706.
DOI Link 2306
BibRef

Hanuš, J.[Jan], Slezák, L.[Lukáš], Fabiánek, T.[Tomáš], Fajmon, L.[Lukáš], Hanousek, T.[Tomáš], Janoutová, R.[Ružena], Kopkáne, D.[Daniel], Novotný, J.[Jan], Pavelka, K.[Karel], Pikl, M.[Miroslav], Zemek, F.[František], Homolová, L.[Lucie],
Flying Laboratory of Imaging Systems: Fusion of Airborne Hyperspectral and Laser Scanning for Ecosystem Research,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
BibRef

Cao, L.P.[Li-Peng], He, Y.S.[Yan-Song], Luo, Y.[Yugong], Chen, J.[Jian],
Layered SOTIF Analysis and 3 sigma-Criterion-Based Adaptive EKF for Lidar-Based Multi-Sensor Fusion Localization System on Foggy Days,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
BibRef

Chang, X.P.[Xue-Peng], Pan, H.H.[Hui-Hui], Sun, W.C.[Wei-Chao], Gao, H.J.[Hui-Jun],
A Multi-Phase Camera-LiDAR Fusion Network for 3D Semantic Segmentation With Weak Supervision,
CirSysVideo(33), No. 8, August 2023, pp. 3737-3746.
IEEE DOI 2308
Point cloud compression, Semantic segmentation, Laser radar, Annotations, Semantics, Robustness, Autonomous driving, weak supervision BibRef

Klein, D.S.[Devi S.], Lago, M.A.[Miguel A.], Abbey, C.K.[Craig K.], Eckstein, M.P.[Miguel P.],
A 2D Synthesized Image Improves the 3D Search for Foveated Visual Systems,
MedImg(42), No. 8, August 2023, pp. 2176-2188.
IEEE DOI 2308
Visualization, Observers, Monitoring, Biomedical monitoring, Solid modeling, Location awareness, Visual search, model observer, 2D-S BibRef

Jonassen, V.O.[Vetle O.], Kjørsvik, N.S.[Narve S.], Gjevestad, J.G.O.[Jon Glenn Omholt],
Scalable hybrid adjustment of images and LiDAR point clouds,
PandRS(202), 2023, pp. 652-662.
Elsevier DOI 2308
LiDAR, Photogrammetry, Hybrid adjustment, Time segmentation, Matching, Voxel BibRef

Jonassen, V.O.[Vetle O.], Kjørsvik, N.S.[Narve S.], Blankenberg, L.E.[Leif Erik], Gjevestad, J.G.O.[Jon Glenn Omholt],
Aerial Hybrid Adjustment of LiDAR Point Clouds, Frame Images, and Linear Pushbroom Images,
RS(16), No. 17, 2024, pp. 3179.
DOI Link 2409
BibRef

Li, W.J.[Wen-Jie], Liu, J.[Jia], Hao, W.[Wei], Liu, H.S.[Hai-Song], Ren, D.[Dayong], Wang, Y.Y.[Yan-Yan], Chen, L.J.[Li-Jun],
Online deep Bingham network for probabilistic orientation estimation,
IET-CV(17), No. 6, 2023, pp. 663-675.
DOI Link 2310
pose etimation, probability, robot vision BibRef

Liu, H.S.[Hai-Song], Lu, T.[Tao], Xu, Y.H.[Yi-Hui], Liu, J.[Jia], Wang, L.M.[Li-Min],
Learning Optical Flow and Scene Flow With Bidirectional Camera-LiDAR Fusion,
PAMI(46), No. 4, April 2024, pp. 2378-2395.
IEEE DOI 2403
Optical flow, Artificial neural networks, Image motion analysis, Pipelines, Laser radar, Multi-modal, camera-LiDAR fusion, autonomous driving BibRef

Liu, H.S.[Hai-Song], Lu, T.[Tao], Xu, Y.H.[Yi-Hui], Liu, J.[Jia], Li, W.J.[Wen-Jie], Chen, L.J.[Li-Jun],
CamLiFlow: Bidirectional Camera-LiDAR Fusion for Joint Optical Flow and Scene Flow Estimation,
CVPR22(5781-5791)
IEEE DOI 2210
Image motion analysis, Art, Fuses, Estimation, Feature extraction, Low-level vision, 3D from multi-view and sensors, Scene analysis and understanding BibRef

Sato, S.[Shogo], Yao, Y.[Yasuhiro], Yoshida, T.[Taiga], Ando, S.[Shingo], Shimamura, J.[Jun],
Shadow Detection Based on Luminance-LiDAR Intensity Uncorrelation,
IEICE(E106-D), No. 9, September 2023, pp. 1556-1563.
WWW Link. 2310
BibRef

Dong, W.Q.[Wen-Qian], Yang, T.[Teng], Qu, J.[Jiahui], Zhang, T.[Tian], Xiao, S.[Song], Li, Y.S.[Yun-Song],
Joint Contextual Representation Model-Informed Interpretable Network With Dictionary Aligning for Hyperspectral and LiDAR Classification,
CirSysVideo(33), No. 11, November 2023, pp. 6804-6818.
IEEE DOI 2311
BibRef

Zhu, H.Q.[Han-Qi], Deng, J.J.[Jia-Jun], Zhang, Y.[Yu], Ji, J.M.[Jian-Min], Mao, Q.Y.[Qiu-Yu], Li, H.Q.[Hou-Qiang], Zhang, Y.Y.[Yan-Yong],
VPFNet: Improving 3D Object Detection With Virtual Point Based LiDAR and Stereo Data Fusion,
MultMed(25), 2023, pp. 5291-5304.
IEEE DOI 2311
BibRef

Zhang, L.[Lei], Li, X.[Xu], Tang, K.[Kaichen], Jiang, Y.Z.[Yun-Zhe], Yang, L.[Liu], Zhang, Y.G.[Yong-Gang], Chen, X.[Xianyi],
FS-Net: LiDAR-Camera Fusion with Matched Scale for 3D Object Detection in Autonomous Driving,
ITS(24), No. 11, November 2023, pp. 12154-12165.
IEEE DOI 2311
BibRef

Tu, D.[Diantao], Cui, H.[Hainan], Shen, S.H.[Shu-Han],
PanoVLM: Low-Cost and accurate panoramic vision and LiDAR fused mapping,
PandRS(206), 2023, pp. 149-167.
Elsevier DOI Code:
WWW Link. 2312
Panoramic camera, Line feature matching, Camera-liDAR joint optimization, Structure-from-Motion, Multi-view stereo BibRef

Yu, Y.[Ying], Fan, S.[Song], Li, L.[Lei], Wang, T.[Tao], Li, L.[Li],
Automatic Targetless Monocular Camera and LiDAR External Parameter Calibration Method for Mobile Robots,
RS(15), No. 23, 2023, pp. 5560.
DOI Link 2312
BibRef

Huang, J.[Jing], Zhang, Y.H.[Ying-Hao], Yang, F.[Fang], Chai, L.[Li],
Attention-Guided Fusion and Classification for Hyperspectral and LiDAR Data,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Xu, H.T.[Hai-Tao], Zheng, T.[Tie], Liu, Y.Z.[Yu-Zhe], Zhang, Z.Y.[Zhi-Yuan], Xue, C.B.[Chang-Bin], Li, J.J.[Jiao-Jiao],
A Joint Convolutional Cross ViT Network for Hyperspectral and Light Detection and Ranging Fusion Classification,
RS(16), No. 3, 2024, pp. 489.
DOI Link 2402
BibRef

Wang, M.H.[Min-Hui], Sun, Y.X.[Ya-Xiu], Xiang, J.H.[Jian-Hong], Sun, R.[Rui], Zhong, Y.[Yu],
Joint Classification of Hyperspectral and LiDAR Data Based on Adaptive Gating Mechanism and Learnable Transformer,
RS(16), No. 6, 2024, pp. 1080.
DOI Link 2403
BibRef

Wang, H.Y.[Hao-Yu], Cheng, Y.[Yuhu], Liu, X.M.[Xiao-Min], Wang, X.S.[Xue-Song],
Reinforcement Learning Based Markov Edge Decoupled Fusion Network for Fusion Classification of Hyperspectral and LiDAR,
MultMed(26), 2024, pp. 7174-7187.
IEEE DOI 2405
Feature extraction, Laser radar, Task analysis, Topology, Data mining, Data integration, Remote sensing, graph learning BibRef

Zhang, H.[Han], Ran, X.X.[Xiao-Xiao], Zhou, W.[Wujie],
Self-Knowledge Distillation-Based Staged Extraction and Multiview Collection Network for RGB-D Mirror Segmentation,
SPLetters(31), 2024, pp. 1029-1033.
IEEE DOI 2405
Feature extraction, Mirrors, Data mining, Semantic segmentation, Convolution, Signal processing algorithms, Decoding, self-knowledge distillation BibRef

Han, Y.[Yu], Salido-Monzú, D.[David], Butt, J.A.[Jemil Avers], Schweizer, S.[Sebastian], Wieser, A.[Andreas],
A feature selection method for multimodal multispectral LiDAR sensing,
PandRS(212), 2024, pp. 42-57.
Elsevier DOI Code:
WWW Link. 2406
Laser scanning, MM LiDAR, Material classification, Multiclass group feature selection, Structural sparsity BibRef

He, Z.T.[Zong-Tao], Wang, L.[Liuyi], Dang, R.H.[Rong-Hao], Li, S.[Shu], Yan, Q.Q.[Qing-Qing], Liu, C.J.[Cheng-Ju], Chen, Q.J.[Qi-Jun],
Learning Depth Representation From RGB-D Videos by Time-Aware Contrastive Pre-Training,
CirSysVideo(34), No. 6, June 2024, pp. 4143-4158.
IEEE DOI 2406
Task analysis, Artificial intelligence, Videos, Training, Databases, Visualization, Feature extraction, Depth representation, embodied AI BibRef

Kim, T.L.[Taek-Lim], Park, T.H.[Tae-Hyoung],
Reinforcement Learning and Genetic Algorithm-Based Network Module for Camera-LiDAR Detection,
RS(16), No. 13, 2024, pp. 2287.
DOI Link 2407
BibRef

Chen, S.T.[Shu-Ting], Su, Y.F.[Yan-Fei], Lai, B.[Baiqi], Cai, L.[Luwei], Hong, C.X.[Cheng-Xi], Li, L.[Li], Qiu, X.L.[Xiu-Liang], Jia, H.[Hong], Liu, W.Q.[Wei-Quan],
2D3D-DescNet: Jointly Learning 2D and 3D Local Feature Descriptors for Cross-Dimensional Matching,
RS(16), No. 13, 2024, pp. 2493.
DOI Link 2407
BibRef

Wang, J.[Jian], Li, F.[Fan], An, Y.[Yi], Zhang, X.C.[Xu-Chong], Sun, H.B.[Hong-Bin],
Toward Robust LiDAR-Camera Fusion in BEV Space via Mutual Deformable Attention and Temporal Aggregation,
CirSysVideo(34), No. 7, July 2024, pp. 5753-5764.
IEEE DOI 2407
Laser radar, Cameras, Three-dimensional displays, Feature extraction, Detectors, Sensors, Object detection, model robustness BibRef

Li, Z.[Zirui], Liu, R.[Runbang], Sun, L.[Le], Zheng, Y.H.[Yu-Hui],
Multi-Feature Cross Attention-Induced Transformer Network for Hyperspectral and LiDAR Data Classification,
RS(16), No. 15, 2024, pp. 2775.
DOI Link 2408
BibRef

Liu, Z.[Zhao], Fu, Z.L.[Zhong-Liang], Li, G.[Gang], Zhang, S.Y.[Sheng-Yuan],
A novel multi-model 3D object detection framework with adaptive voxel-image feature fusion,
IET-CV(18), No. 5, 2024, pp. 640-651.
DOI Link 2408
image sensors, neural net architecture, object detection, sensor fusion BibRef

Wang, A.[Aili], Dai, S.Y.[Shi-Yu], Wu, H.B.[Hai-Bin], Iwahori, Y.[Yuji],
Multimodal Semantic Collaborative Classification for Hyperspectral Images and LiDAR Data,
RS(16), No. 16, 2024, pp. 3082.
DOI Link 2408
BibRef

An, P.[Pei], Hu, X.Z.[Xu-Zhong], Ding, J.F.[Jun-Feng], Zhang, J.[Jun], Ma, J.[Jie], Yang, Y.[You], Liu, Q.[Qiong],
OL-Reg: Registration of Image and Sparse LiDAR Point Cloud With Object-Level Dense Correspondences,
CirSysVideo(34), No. 8, August 2024, pp. 7523-7536.
IEEE DOI Code:
WWW Link. 2408
Point cloud compression, Laser radar, Cameras, Calibration, Odometry, Circuits and systems, Light detection and ranging, image, camera re-localization BibRef

Zhang, J.Q.[Jia-Qing], Lei, J.[Jie], Xie, W.Y.[Wei-Ying], Yang, G.[Geng], Li, D.[Daixun], Li, Y.S.[Yun-Song],
Multimodal Informative ViT: Information Aggregation and Distribution for Hyperspectral and LiDAR Classification,
CirSysVideo(34), No. 8, August 2024, pp. 7643-7656.
IEEE DOI Code:
WWW Link. 2408
Feature extraction, Task analysis, Transformers, Mutual information, Laser radar, Redundancy, Data mining, self-distillation BibRef

Pan, H.Z.[Hai-Zhu], Li, X.[Xuan], Ge, H.[Haimiao], Wang, L.G.[Li-Guo], Shi, C.P.[Cui-Ping],
A Hierarchical Coarse-Fine Adaptive Fusion Network for the Joint Classification of Hyperspectral and LiDAR Data,
RS(16), No. 21, 2024, pp. 4029.
DOI Link 2411
BibRef

Wang, R.[Rui], Ye, X.X.[Xiao-Xi], Huang, Y.[Yao], Ju, M.[Ming], Xiang, W.[Wei],
GASSF-Net: Geometric Algebra Based Spectral-Spatial Hierarchical Fusion Network for Hyperspectral and LiDAR Image Classification,
RS(16), No. 20, 2024, pp. 3825.
DOI Link 2411
BibRef

Li, S.[Sai], Huang, S.[Shuo],
AFA-Mamba: Adaptive Feature Alignment with Global-Local Mamba for Hyperspectral and LiDAR Data Classification,
RS(16), No. 21, 2024, pp. 4050.
DOI Link 2411
BibRef

Dharmasiri, A.[Amaya], Naseer, M.[Muzammal], Khan, S.[Salman], Khan, F.S.[Fahad Shahbaz],
Cross-Modal Self-Training: Aligning Images and Pointclouds to learn Classification without Labels,
L3D24(708-717)
IEEE DOI 2410
Point cloud compression, Representation learning, Adaptation models, Solid modeling, Computational modeling, 2D multiview BibRef

Tao, T.[Tang], Wang, G.[Guangrun], Lao, Y.X.[Yi-Xing], Chen, P.[Peng], Liu, J.[Jie], Lin, L.[Liang], Yu, K.C.[Kai-Cheng], Liang, X.D.[Xiao-Dan],
AlignMiF: Geometry-Aligned Multimodal Implicit Field for LiDAR-Camera Joint Synthesis,
CVPR24(21230-21240)
IEEE DOI Code:
WWW Link. 2410
Geometry, Laser radar, Sensor phenomena and characterization, Network architecture, Neural radiance field, Cameras, AlignMiF, LiDAR-Camera Joint Synthesis BibRef

Gunn, J.[James], Lenyk, Z.[Zygmunt], Sharma, A.[Anuj], Donati, A.[Andrea], Buburuzan, A.[Alexandru], Redford, J.[John], Mueller, R.[Romain],
Lift-Attend-Splat: Bird's-eye-view camera-lidar fusion using transformers,
WAD24(4526-4536)
IEEE DOI 2410
Solid modeling, Laser radar, Attention mechanisms, Estimation, Object detection, Cameras BibRef

Wu, L.[Lemeng], Wang, D.[Dilin], Li, M.[Meng], Xiong, Y.Y.[Yun-Yang], Krishnamoorthi, R.[Raghuraman], Liu, Q.[Qiang], Chandra, V.[Vikas],
PathFusion: Path-Consistent Lidar-Camera Deep Feature Fusion,
3DV24(313-323)
IEEE DOI 2408
Point cloud compression, Laser radar, Semantics, Transforms, Cameras, Feature extraction, 3D detection, feature fusion BibRef

Zhang, Y.C.[Yu-Cheng], Fukuda, M.[Masaki], Ishii, Y.[Yasunori], Ohshima, K.[Kyoko], Yamashita, T.[Takayoshi],
PALF: Pre-Annotation and Camera-LiDAR Late Fusion for the Easy Annotation of Point Clouds,
MVA23(1-5)
DOI Link 2403
Point cloud compression, Deep learning, Training, Backpropagation, Image resolution, Annotations BibRef

Li, M.[Minhao], Qin, Z.[Zheng], Gao, Z.[Zhirui], Yi, R.[Renjiao], Zhu, C.Y.[Chen-Yang], Guo, Y.L.[Yu-Lan], Xu, K.[Kai],
2D3D-MATR: 2D-3D Matching Transformer for Detection-free Registration between Images and Point Clouds,
ICCV23(14082-14092)
IEEE DOI Code:
WWW Link. 2401
BibRef

Kim, M.[Minjung], Koo, J.[Junseo], Kim, G.[Gunhee],
EP2P-Loc: End-to-End 3D Point to 2D Pixel Localization for Large-Scale Visual Localization,
ICCV23(21470-21480)
IEEE DOI 2401
BibRef

Qin, Y.[Yiran], Wang, C.Q.[Chao-Qun], Kang, Z.J.[Zi-Jian], Ma, N.N.[Ning-Ning], Li, Z.[Zhen], Zhang, R.M.[Rui-Mao],
SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection,
ICCV23(21957-21967)
IEEE DOI Code:
WWW Link. 2401
BibRef

Sbrolli, C.[Cristian], Cudrano, P.[Paolo], Matteucci, M.[Matteo],
CISPC: Embedding Images and Point Clouds in a Joint Concept Space by Contrastive Learning,
CIAP23(II:468-476).
Springer DOI 2312
BibRef

Singh, A.D.[Akash Deep], Ba, Y.H.[Yun-Hao], Sarker, A.[Ankur], Zhang, H.[Howard], Kadambi, A.[Achuta], Soatto, S.[Stefano], Srivastava, M.[Mani], Wong, A.[Alex],
Depth Estimation from Camera Image and mmWave Radar Point Cloud,
CVPR23(9275-9285)
IEEE DOI 2309
BibRef

Zendel, O.[Oliver], Huemer, J.[Johannes], Murschitz, M.[Markus], Dominguez, G.F.[Gustavo Fernandez], Lobe, A.[Amadeus],
Joint Camera and LiDAR Risk Analysis,
WAD23(88-97)
IEEE DOI 2309
BibRef

Chen, X.Y.[Xuan-Yao], Zhang, T.Y.[Tian-Yuan], Wang, Y.[Yue], Wang, Y.L.[Yi-Lun], Zhao, H.[Hang],
FUTR3D: A Unified Sensor Fusion Framework for 3D Detection,
WAD23(172-181)
IEEE DOI 2309
BibRef

Jiao, Y.[Yang], Jie, Z.Q.[Ze-Qun], Chen, S.X.[Shao-Xiang], Chen, J.J.[Jing-Jing], Ma, L.[Lin], Jiang, Y.G.[Yu-Gang],
MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection,
CVPR23(21643-21652)
IEEE DOI 2309
BibRef

Yu, K.C.[Kai-Cheng], Tao, T.[Tang], Xie, H.W.[Hong-Wei], Lin, Z.W.[Zhi-Wei], Liang, T.T.[Ting-Ting], Wang, B.[Bing], Chen, P.[Peng], Hao, D.[Dayang], Wang, Y.T.[Yong-Tao], Liang, X.D.[Xiao-Dan],
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection,
E2EAD23(3188-3198)
IEEE DOI 2309
BibRef

Yin, H.X.[Han-Xi], Deng, L.[Lei], Chen, Z.X.[Zhi-Xiang], Chen, B.[Baohua], Sun, T.[Ting], Xie, Y.S.[Yu-Seng], Xiao, J.W.[Jun-Wei], Fu, Y.[Yeyu], Deng, S.X.[Shui-Xin], Li, X.[Xiu],
LSMD-Net: Lidar-stereo Fusion with Mixture Density Network for Depth Sensing,
ACCV22(I:89-105).
Springer DOI 2307
BibRef

Li, Y.J.[Yi-Jin], Liu, X.Y.[Xin-Yang], Dong, W.Q.[Wen-Qi], Zhou, H.[Han], Bao, H.J.[Hu-Jun], Zhang, G.F.[Guo-Feng], Zhang, Y.[Yinda], Cui, Z.P.[Zhao-Peng],
DELTAR: Depth Estimation from a Light-Weight ToF Sensor and RGB Image,
ECCV22(I:619-636).
Springer DOI 2211
BibRef

Peng, L.[Liang], Liu, F.[Fei], Yu, Z.X.[Zheng-Xu], Yan, S.[Senbo], Deng, D.[Dan], Yang, Z.[Zheng], Liu, H.F.[Hai-Feng], Cai, D.[Deng],
Lidar Point Cloud Guided Monocular 3D Object Detection,
ECCV22(I:123-139).
Springer DOI 2211
BibRef

Bensaïd, D.[David], Bracha, A.[Amit], Kimmel, R.[Ron],
Partial Shape Similarity by Multi-Metric Hamiltonian Spectra Matching,
SSVM23(717-729).
Springer DOI 2307
BibRef

Rotstein, N.[Noam], Bracha, A.[Amit], Kimmel, R.[Ron],
Multimodal Colored Point Cloud to Image Alignment,
CVPR22(6646-6656)
IEEE DOI 2210
Point cloud compression, Solid modeling, Image color analysis, Supervised learning, Pose estimation, Pipelines, RGBD sensors and analytics BibRef

Li, Y.W.[Ying-Wei], Yu, A.W.[Adams Wei], Meng, T.J.[Tian-Jian], Caine, B.[Ben], Ngiam, J.[Jiquan], Peng, D.[Daiyi], Shen, J.Y.[Jun-Yang], Lu, Y.F.[Yi-Feng], Zhou, D.[Denny], Le, Q.V.[Quoc V.], Yuille, A.L.[Alan L.], Tan, M.X.[Ming-Xing],
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection,
CVPR22(17161-17170)
IEEE DOI 2210
Solid modeling, Laser radar, Object detection, Cameras, Feature extraction, Data models, 3D from multi-view and sensors BibRef

Bai, X.Y.[Xu-Yang], Hu, Z.[Zeyu], Zhu, X.G.[Xin-Ge], Huang, Q.Q.[Qing-Qiu], Chen, Y.L.[Yi-Lun], Fu, H.[Hangbo], Tai, C.L.[Chiew-Lan],
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers,
CVPR22(1080-1089)
IEEE DOI 2210
Point cloud compression, Laser radar, Sensor fusion, Transformers, Robustness, Sensors, Recognition: detection, categorization, Navigation and autonomous driving BibRef

Du, P.F.[Peng-Fei], Gao, Y.[Yali], Li, X.Y.[Xiao-Yong],
Bi-attention Modal Separation Network for Multimodal Video Fusion,
MMMod22(I:585-598).
Springer DOI 2203
BibRef

Jung, H.J.[Hyun-Jun], Brasch, N.[Nikolas], Leonardis, A.[Aleš], Navab, N.[Nassir], Busam, B.[Benjamin],
Wild ToFu: Improving Range and Quality of Indirect Time-of-Flight Depth with RGB Fusion in Challenging Environments,
3DV21(239-248)
IEEE DOI 2201
Time-frequency analysis, Image resolution, Pipelines, Imaging, Estimation, Sensor fusion, ToF, Time of Flight, Depth, Fusion BibRef

Kalinowski, P., Both, F., Luhmann, T., Warnke, U.,
Data Fusion of Historical Photographs with Modern 3d Data for An Archaeological Excavation - Concept and First Results,
ISPRS21(B2-2021: 571-576).
DOI Link 2201
BibRef

Dursun, I., Varlik, A.,
Integration of Data Obtained By Photogrammetric Methods Such As A Terrestrial Laser Scanner and UAV System and Use in 3d City Models: The Case of KÖycegiz Campus,
SmartCityApp21(187-192).
DOI Link 2201
BibRef

Castillo, E.S.[E. Sanchez], Griffiths, D., Boehm, J.,
Semantic Segmentation of Terrestrial Lidar Data Using Co-registered RGB Data,
ISPRS21(B2-2021: 223-229).
DOI Link 2201
BibRef

Bose, R.[Rupak], Pande, S.[Shivam], Banerjee, B.[Biplab],
Two Headed Dragons: Multimodal Fusion and Cross Modal Transactions,
ICIP21(2893-2897)
IEEE DOI 2201
Laser radar, Image processing, Data integration, Data models, Data mining, Character recognition, Hyperspectral, LiDAR, cross-modal inferences BibRef

Ciubotariu, G.[George], Tomescu, V.I.[Vlad-Ioan], Czibula, G.[Gabriela],
Enhancing the Performance of Image Classification Through Features Automatically Learned from Depth-Maps,
CVS21(68-81).
Springer DOI 2109
BibRef

Mahmoud, A.[Anas], Waslander, S.L.[Steven L.],
Sequential Fusion via Bounding Box and Motion PointPainting for 3D Objection Detection,
CRV21(9-16)
IEEE DOI 2108
Fusion RGB and Lidar. Image segmentation, Laser radar, Motion segmentation, Semantics, Detectors, Streaming media, temporal aggregation BibRef

Su, Y.N.[Ying-Na], Ding, Y.Q.[Ya-Qing], Yang, J.[Jian], Kong, H.[Hui],
A two-step approach to Lidar-Camera calibration,
ICPR21(6834-6841)
IEEE DOI 2105
Laser radar, Closed-form solutions, Robot kinematics, Robot vision systems, Cameras, Calibration BibRef

Peng, B., Yu, Z., Lei, J., Song, J.,
Attention-Guided Fusion Network of Point Cloud and Multiple Views for 3D Shape Recognition,
VCIP20(185-188)
IEEE DOI 2102
Shape, Feature extraction, Fuses, Solid modeling, Task analysis, Correlation, 3D Shape, Multi-View BibRef

Megahed, Y., Yan, W.Y., Shaker, A.,
Semi-automatic Approach for Optical and Lidar Data Integration Using Phase Congruency Model At Multiple Resolutions,
ISPRS20(B3:611-618).
DOI Link 2012
BibRef

Mohla, S., Pande, S., Banerjee, B., Chaudhuri, S.,
FusAtNet: Dual Attention based SpectroSpatial Multimodal Fusion Network for Hyperspectral and LiDAR Classification,
PBVS20(416-425)
IEEE DOI 2008
Feature extraction, Laser radar, Task analysis, Hyperspectral sensors, Sensors, Machine learning BibRef

Siddiqui, T.A., Madhok, R., O'Toole, M.,
An Extensible Multi-Sensor Fusion Framework for 3D Imaging,
AutoDrive20(4344-4353)
IEEE DOI 2008
Laser radar, Cameras, Photonics, Noise measurement, Task analysis BibRef

Leite, P.N.[Pedro Nuno], Silva, R.J.[Renato Jorge], Campos, D.F.[Daniel Filipe], Pinto, A.M.[Andry Maykol],
Dense Disparity Maps from RGB and Sparse Depth Information Using Deep Regression Models,
ICIAR20(I:379-392).
Springer DOI 2007
BibRef

Nicastro, A., Clark, R., Leutenegger, S.,
X-Section: Cross-Section Prediction for Enhanced RGB-D Fusion,
ICCV19(1517-1526)
IEEE DOI 2004
cameras, convolutional neural nets, image fusion, image reconstruction, learning (artificial intelligence), Pipelines BibRef

Qiu, J.X.[Jia-Xiong], Cui, Z.P.[Zhao-Peng], Zhang, Y.[Yinda], Zhang, X.[Xingdi], Liu, S.C.[Shuai-Cheng], Zeng, B.[Bing], Pollefeys, M.[Marc],
DeepLiDAR: Deep Surface Normal Guided Depth Prediction for Outdoor Scene From Sparse LiDAR Data and Single Color Image,
CVPR19(3308-3317).
IEEE DOI 2002
BibRef

Cheng, X.L.[Xue-Lian], Zhong, Y.[Yiran], Dai, Y.C.[Yu-Chao], Ji, P.[Pan], Li, H.D.[Hong-Dong],
Noise-Aware Unsupervised Deep Lidar-Stereo Fusion,
CVPR19(6332-6341).
IEEE DOI 2002
BibRef

Eslami, M., Saadatseresht, M.,
A Novel Tie Point Based Strategy for Point Cloud and Imagery Data Fine Registration,
SMPR19(331-334).
DOI Link 1912
BibRef

Shaw, L., Helmholz, P., Belton, D., Addy, N.,
Comparison of UAV Lidar and Imagery for Beach Monitoring,
UAV-g19(589-596).
DOI Link 1912
BibRef

Davidson, L., Mills, J.P., Haynes, I., Augarde, C., Bryan, P., Douglas, M.,
Airborne to UAS Lidar: An Analysis of UAS Lidar Ground Control Targets,
UAV-g19(255-262).
DOI Link 1912
BibRef

Kozonek, N., Zeller, N., Bock, H., Pfeifle, M.,
On The Fusion of Camera and Lidar for 3d Object Detection And Classification,
PIA19(149-156).
DOI Link 1912
BibRef

Daneshtalab, S., Rastiveis, H., Hosseiny, B.,
Cnn-based Feature-level Fusion of Very High Resolution Aerial Imagery And Lidar Data,
SMPR19(279-284).
DOI Link 1912
BibRef

Kalantar, B., Ueda, N., Al-Najjar, H.A.H., Moayedi, H., Halin, A.A., Mansor, S.,
UAV and Lidar Image Registration: a Surf-based Approach for Ground Control Points Selection,
UAV-g19(413-418).
DOI Link 1912
BibRef

Rambach, J.[Jason], Lesur, P.[Paul], Pagani, A.[Alain], Stricker, D.[Didier],
SlamCraft: Dense Planar RGB Monocular SLAM,
MVA19(1-6)
DOI Link 1911
Planar regions from RGB, fuse with point cloud. augmented reality, convolutional neural nets, mobile robots, neurocontrollers, robot vision, sensors, SLAM (robots), SlamCraft, Estimation BibRef