11.2.4.1 Depth Object Detection, 3D Object Detection

Chapter Contents (Back)
Object Detection. More than just segmentation.

Thonnat, M.,
Semantic Interpretation of 3-D Stereo Data: Finding the Main Structures,
PRAI(2), 1988, pp. 509-525. BibRef 8800
Earlier: ICPR86(1051-1054). BibRef

Ma, R., Thonnat, M.,
Object Detection in Outdoor Scenes by Disparity Map Segmentation,
ICPR92(I:546-549).
IEEE DOI BibRef 9200

Chen, X.[Xujian], Teoh, E.K.[Eam Khwang],
3D object segmentation using B-Surface,
IVC(23), No. 14, 12 December 2005, pp. 1237-1249.
Elsevier DOI 0601
BibRef
Earlier:
3D growing deformable B-surface model for object detection,
ICARCV04(I: 357-362).
IEEE DOI 0412
Slice by slice. BibRef

Reisert, M.[Marco], Burkhardt, H.[Hans],
Complex Derivative Filters,
IP(17), No. 12, December 2008, pp. 2265-2274.
IEEE DOI 0811
BibRef

Reisert, M.[Marco], Burkhardt, H.[Hans],
Equivariant Holomorphic Filters for Contour Denoising and Rapid Object Detection,
IP(17), No. 2, February 2008, pp. 190-203.
IEEE DOI 0801
BibRef

Reisert, M.[Marco], Ronneberger, O.[Olaf], Burkhardt, H.[Hans],
Holomorphic Filters for Object Detection,
DAGM07(304-313).
Springer DOI 0709
BibRef
And:
A Fast and Reliable Coin Recognition System,
DAGM07(415-424).
Springer DOI 0709
BibRef

Reisert, M.[Marco], Burkhardt, H.[Hans],
Efficient Tensor Voting with 3D tensorial harmonics,
Tensor08(1-7).
IEEE DOI 0806
BibRef

Reisert, M.[Marco], Burkhardt, H.[Hans],
Harmonic Filters for Generic Feature Detection in 3D,
DAGM09(131-140).
Springer DOI 0909
See also Harmonic Filters for 3D Multichannel Data: Rotation Invariant Detection of Mitoses in Colorectal Cancer. BibRef

Reisert, M.[Marco], Burkhardt, H.[Hans],
Using Irreducible Group Representations for Invariant 3D Shape Description,
DAGM06(132-141).
Springer DOI 0610
BibRef
And:
Feature Selection for Retrieval Purposes,
ICIAR06(I: 661-672).
Springer DOI 0610
BibRef
Earlier:
Invariant Features for 3D-Data based on Group Integration using Directional Information and Spherical Harmonic Expansion,
ICPR06(IV: 206-209).
IEEE DOI 0609
BibRef

Velizhev, A., Shapovalov, R., Schindler, K.,
Implicit Shape Models for Object Detection In 3d Point Clouds,
AnnalsPRS(I-3), No. 2012, pp. 179-184.
HTML Version. 1209
BibRef

Yang, B.[Bisheng], Dong, Z.[Zhen],
A shape-based segmentation method for mobile laser scanning point clouds,
PandRS(81), No. 1, July 2013, pp. 19-30.
Elsevier DOI 1306
Point classification; Object segmentation; Mobile laser scanning; Object extraction BibRef

Boochs, F.[Frank], Kern, F.[Fredie], Schütze, R.[Rainer], Marbs, A.[Andreas],
Approaches for geometrical and semantic modelling of huge unstructured 3D point clouds,
PFG(2009), No. 1, 2009, pp. 65-77.
WWW Link. 1211
BibRef

Ponciano, J.J.[Jean-Jacques], Trémeau, A.[Alain], Boochs, F.[Frank],
Automatic Detection of Objects in 3D Point Clouds Based on Exclusively Semantic Guided Processes,
IJGI(8), No. 10, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Boochs, F.[Frank], Karmacharya, A., Marbs, A.,
Knowledge-based Object Detection In Laser Scanning Point Clouds,
ISPRS12(XXXIX-B3:91-96).
DOI Link 1209
BibRef

Truong, H.Q.[Hung Quoc], Ben Hmida, H.[Helmi], Marbs, A.[Andreas], Boochs, F.[Frank],
Integration of knowledge into the detection of objects in point clouds,
PCVIA10(B:143).
PDF File. 1009
BibRef

Kiforenko, L.[Lilita], Drost, B.[Bertram], Tombari, F.[Federico], Krüger, N.[Norbert], Buch, A.G.[Anders Glent],
A performance evaluation of point pair features,
CVIU(166), No. 1, 2018, pp. 66-80.
Elsevier DOI 1712
PPF BibRef

Kiforenko, L.[Lilita], Buch, A.G.[Anders Glent], Krüger, N.[Norbert],
Object Detection Using a Combination of Multiple 3D Feature Descriptors,
CVS15(343-353).
Springer DOI 1507
BibRef

Fu, J.S.[Jun-Sheng], Kämäräinen, J.K.[Joni-Kristian], Buch, A.G.[Anders Glent], Krüger, N.[Norbert],
Indoor Objects and Outdoor Urban Scenes Recognition by 3D Visual Primitives,
BD3DCV14(270-285).
Springer DOI 1504
BibRef

Fehr, D.[Duc], Beksi, W.J.[William J.], Zermas, D.[Dimitris], Papanikolopoulos, N.[Nikolaos],
Covariance based point cloud descriptors for object detection and recognition,
CVIU(142), No. 1, 2016, pp. 80-93.
Elsevier DOI 1512
RGB-D data BibRef

Wang, Z.L.[Zi-Lei], Xiang, D., Hou, S.H.[Sai-Hui], Wu, F.[Feng],
Background-Driven Salient Object Detection,
MultMed(19), No. 4, April 2017, pp. 750-762.
IEEE DOI 1704
Benchmark testing BibRef

Hou, S.H.[Sai-Hui], Wang, Z.L.[Zi-Lei], Wu, F.[Feng],
Deeply Exploit Depth Information for Object Detection,
Robust16(1092-1100)
IEEE DOI 1612
BibRef

Qu, L., He, S., Zhang, J., Tian, J., Tang, Y., Yang, Q.,
RGBD Salient Object Detection via Deep Fusion,
IP(26), No. 5, May 2017, pp. 2274-2285.
IEEE DOI 1704
Electronic mail BibRef

Wang, A., Wang, M.,
RGB-D Salient Object Detection via Minimum Barrier Distance Transform and Saliency Fusion,
SPLetters(24), No. 5, May 2017, pp. 663-667.
IEEE DOI 1704
Image color analysis BibRef

Xu, X.Y.[Xiang-Yang], Li, Y.C.[Yun-Cheng], Wu, G.S.[Gang-Shan], Luo, J.B.[Jie-Bo],
Multi-modal deep feature learning for RGB-D object detection,
PR(72), No. 1, 2017, pp. 300-313.
Elsevier DOI 1708
RGB-D, objectness estimation BibRef

Han, J.W.[Jun-Wei], Chen, H.[Hao], Liu, N.[Nian], Yan, C.G.[Cheng-Gang], Li, X.L.[Xue-Long],
CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion,
Cyber(48), No. 11, November 2018, pp. 3171-3183.
IEEE DOI 1810
Object detection, Image color analysis, Adaptation models, Fuses, Biological neural networks, Computer vision, salient object detection BibRef

Chen, H.[Hao], Li, Y.F.[You-Fu], Su, D.[Dan],
Multi-modal fusion network with multi-scale multi-path and cross-modal interactions for RGB-D salient object detection,
PR(86), 2019, pp. 376-385.
Elsevier DOI 1811
BibRef
Earlier:
RGB-D Saliency Detection by Multi-stream Late Fusion Network,
CVS17(459-468).
Springer DOI 1711
RGB-D, Convolutional neural networks, Multi-path, Saliency detection BibRef

Chen, H.[Hao], Li, Y.F.[You-Fu],
Three-Stream Attention-Aware Network for RGB-D Salient Object Detection,
IP(28), No. 6, June 2019, pp. 2825-2835.
IEEE DOI 1905
BibRef
Earlier:
Progressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection,
CVPR18(3051-3060)
IEEE DOI 1812
convolutional neural nets, feature extraction, feature selection, image colour analysis, image fusion, cross-modal cross-level attention. Object detection, Fuses, Saliency detection, Task analysis, BibRef

Chen, H.[Hao], Deng, Y.J.[Yong-Jian], Li, Y.F.[You-Fu], Hung, T.Y.[Tzu-Yi], Lin, G.S.[Guo-Sheng],
RGBD Salient Object Detection via Disentangled Cross-Modal Fusion,
IP(29), 2020, pp. 8407-8416.
IEEE DOI 2008
Image reconstruction, Feature extraction, Object detection, Topology, Image color analysis, Machine learning, saliency detection BibRef

Pahwa, R.S.[Ramanpreet Singh], Lu, J., Jiang, N., Ng, T.T.[Tian Tsong], Do, M.N.[Minh N.],
Locating 3D Object Proposals: A Depth-Based Online Approach,
CirSysVideo(28), No. 3, March 2018, pp. 626-639.
IEEE DOI 1804
computational geometry, image colour analysis, image registration, image sequences, object detection, robot vision BibRef

Li, G., Gan, Y., Wu, H., Xiao, N., Lin, L.,
Cross-Modal Attentional Context Learning for RGB-D Object Detection,
IP(28), No. 4, April 2019, pp. 1591-1601.
IEEE DOI 1901
computer vision, feature extraction, image colour analysis, image representation, learning (artificial intelligence), convolutional neural network BibRef

Chen, C., Huang, H., Chen, C., Zheng, Z., Cheng, H.,
Multi-Scale Guided Mask Refinement for Coarse-to-Fine RGB-D Perception,
SPLetters(26), No. 2, February 2019, pp. 217-221.
IEEE DOI 1902
computer vision, image colour analysis, image segmentation, neural nets, object detection, depth assisted methods, edge-preserving filtering BibRef

Xiao, X., Zhou, Y., Gong, Y.,
RGB-'D' Saliency Detection With Pseudo Depth,
IP(28), No. 5, May 2019, pp. 2126-2139.
IEEE DOI 1903
feature extraction, image colour analysis, stereo image processing, supervised learning, salient object detection BibRef

Huang, R., Xing, Y., Wang, Z.,
RGB-D Salient Object Detection by a CNN With Multiple Layers Fusion,
SPLetters(26), No. 4, April 2019, pp. 552-556.
IEEE DOI 1903
Saliency detection, Detectors, Training, Computational modeling, Benchmark testing, Feature extraction, Fuses, CNN BibRef

Wang, R.Z.[Run-Zhi], Wan, W.H.[Wen-Hui], Wang, Y.K.[Yong-Kang], Di, K.C.[Kai-Chang],
A New RGB-D SLAM Method with Moving Object Detection for Dynamic Indoor Scenes,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Li, G., Liu, Z., Ling, H.,
ICNet: Information Conversion Network for RGB-D Based Salient Object Detection,
IP(29), 2020, pp. 4873-4884.
IEEE DOI 2003
Feature extraction, Correlation, Fuses, Decoding, Object detection, Visualization, Convolution, RGB-D based salient object detection, siamese structure BibRef

Cong, R.M.[Run-Min], Lei, J.J.[Jian-Jun], Fu, H.Z.[Hua-Zhu], Hou, J.H.[Jun-Hui], Huang, Q.M.[Qing-Ming], Kwong, S.[Sam],
Going From RGB to RGBD Saliency: A Depth-Guided Transformation Model,
Cyber(50), No. 8, August 2020, pp. 3627-3639.
IEEE DOI 2007
Saliency detection, Image color analysis, Optimization, Shape, Feature extraction, Task analysis, Object detection, Depth cue, transformation model BibRef

Li, Y.[Ying], Ma, L.F.[Ling-Fei], Tan, W.[Weikai], Sun, C.[Chen], Cao, D.[Dongpu], Li, J.[Jonathan],
GRNet: Geometric relation network for 3D object detection from point clouds,
PandRS(165), 2020, pp. 43-53.
Elsevier DOI 2006
Deep learning, 3D object detection, Point cloud, Geometric relation, Indoor mapping, RGB-D BibRef

Yan, L.[Lin], Liu, K.[Kai], Belyaev, E.[Evgeny], Duan, M.[Meiyu],
RTL3D: real-time LIDAR-based 3D object detection with sparse CNN,
IET-CV(14), No. 5, August 2020, pp. 224-232.
DOI Link 2007
collapse 3D to 2D for initial detection. BibRef

Wang, J.R.[Jia-Rong], Zhu, M.[Ming], Wang, B.[Bo], Sun, D.[Deyao], Wei, H.[Hua], Liu, C.[Changji], Nie, H.T.[Hai-Tao],
KDA3D: Key-Point Densification and Multi-Attention Guidance for 3D Object Detection,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef


Yang, Z., Sun, Y., Liu, S., Jia, J.,
3DSSD: Point-Based 3D Single Stage Object Detector,
CVPR20(11037-11045)
IEEE DOI 2008
Feature extraction, Proposals, Object detection, Detectors, Semantics BibRef

Tu, J., Ren, M., Manivasagam, S., Liang, M., Yang, B., Du, R., Cheng, F., Urtasun, R.,
Physically Realizable Adversarial Examples for LiDAR Object Detection,
CVPR20(13713-13722)
IEEE DOI 2008
Laser radar, Detectors, Autonomous vehicles, Solid modeling, Laser theory BibRef

He, C., Zeng, H., Huang, J., Hua, X., Zhang, L.,
Structure Aware Single-Stage 3D Object Detection From Point Cloud,
CVPR20(11870-11879)
IEEE DOI 2008
Feature extraction, Task analysis, Detectors, Object detection, Periodic structures, Tensile stress BibRef

Hu, P., Ziglar, J., Held, D., Ramanan, D.,
What You See is What You Get: Exploiting Visibility for 3D Object Detection,
CVPR20(10998-11006)
IEEE DOI 2008
Laser radar, Robot sensing systems, Cognition, Object detection BibRef

Qian, R., Garg, D., Wang, Y., You, Y., Belongie, S., Hariharan, B., Campbell, M., Weinberger, K.Q., Chao, W.,
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection,
CVPR20(5880-5889)
IEEE DOI 2008
Detectors, Object detection, Laser radar, Pipelines, Quantization (signal), Estimation BibRef

Liu, N., Zhang, N., Han, J.,
Learning Selective Self-Mutual Attention for RGB-D Saliency Detection,
CVPR20(13753-13762)
IEEE DOI 2008
Fuses, Saliency detection, Data models, Task analysis, Computational modeling, Object detection, Feature extraction BibRef

Piao, Y., Rong, Z., Zhang, M., Ren, W., Lu, H.,
A2dele: Adaptive and Attentive Depth Distiller for Efficient RGB-D Salient Object Detection,
CVPR20(9057-9066)
IEEE DOI 2008
Saliency detection, Bridges, Testing, Object detection, Knowledge engineering, Computer architecture, Training BibRef

Xie, Q., Lai, Y., Wu, J., Wang, Z., Zhang, Y., Xu, K., Wang, J.,
MLCVNet: Multi-Level Context VoteNet for 3D Object Detection,
CVPR20(10444-10453)
IEEE DOI 2008
Object detection, Feature extraction, Task analysis, Machine learning BibRef

Shi, S., Guo, C., Jiang, L., Wang, Z., Shi, J., Wang, X., Li, H.,
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection,
CVPR20(10526-10535)
IEEE DOI 2008
Feature extraction, Proposals, Encoding, Object detection, Aggregates BibRef

Rünz, M., Li, K., Tang, M., Ma, L., Kong, C., Schmidt, T., Reid, I., Agapito, L., Straub, J., Lovegrove, S., Newcombe, R.,
FroDO: From Detections to 3D Objects,
CVPR20(14708-14717)
IEEE DOI 2008
Shape, Decoding, Image reconstruction, Optimization, Simultaneous localization and mapping BibRef

Najibi, M., Lai, G., Kundu, A., Lu, Z., Rathod, V., Funkhouser, T., Pantofaru, C., Ross, D., Davis, L.S., Fathi, A.,
DOPS: Learning to Detect 3D Objects and Predict Their 3D Shapes,
CVPR20(11910-11919)
IEEE DOI 2008
Shape, Object detection, Laser radar, Training, Pipelines BibRef

Vora, S., Lang, A.H., Helou, B., Beijbom, O.,
PointPainting: Sequential Fusion for 3D Object Detection,
CVPR20(4603-4611)
IEEE DOI 2008
Laser radar, Image segmentation, Semantics, Object detection, Pipeline processing, Cameras BibRef

Qi, C.R., Chen, X., Litany, O., Guibas, L.J.,
ImVoteNet: Boosting 3D Object Detection in Point Clouds With Image Votes,
CVPR20(4403-4412)
IEEE DOI 2008
Object detection, Proposals, Feature extraction, Poles and towers, Semantics BibRef

Peng, W., Pan, H., Liu, H., Sun, Y.,
IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision for Autonomous Driving,
CVPR20(13012-13021)
IEEE DOI 2008
Object detection, Laser radar, Estimation, Cameras, Stereo vision BibRef

Ahmed, S.M., Chew, C.M.,
Density-Based Clustering for 3D Object Detection in Point Clouds,
CVPR20(10605-10614)
IEEE DOI 2008
Task analysis, Object detection, Proposals, Semantics, Image segmentation BibRef

Chen, Y., Liu, S., Shen, X., Jia, J.,
DSGN: Deep Stereo Geometry Network for 3D Object Detection,
CVPR20(12533-12542)
IEEE DOI 2008
Feature extraction, Geometry, Object detection, Detectors, Laser radar BibRef

Sun, J., Chen, L., Xie, Y., Zhang, S., Jiang, Q., Zhou, X., Bao, H.,
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation,
CVPR20(10545-10554)
IEEE DOI 2008
Estimation, Object detection, Shape, Laser radar, Detectors BibRef

Fu, K., Fan, D., Ji, G., Zhao, Q.,
JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection,
CVPR20(3049-3059)
IEEE DOI 2008
Feature extraction, Adaptation models, Object detection, Computer architecture, Training, Robustness, Decoding BibRef

Zhang, M., Ren, W., Piao, Y., Rong, Z., Lu, H.,
Select, Supplement and Focus for RGB-D Saliency Detection,
CVPR20(3469-3478)
IEEE DOI 2008
Feature extraction, Saliency detection, Image edge detection, Task analysis, Fuses, Object detection, Computer vision BibRef

Ye, M., Xu, S., Cao, T.,
HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection,
CVPR20(1628-1637)
IEEE DOI 2008
Feature extraction, Object detection, Laser radar, Encoding, Aggregates BibRef

Shi, W., Rajkumar, R.,
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud,
CVPR20(1708-1716)
IEEE DOI 2008
Neural networks, Object detection, Feature extraction, Convolution, Laser radar, Shape BibRef

Chen, J.T.[Jin-Tai], Lei, B.W.[Bi-Wen], Song, Q.Y.[Qing-Yu], Ying, H.C.[Hao-Chao], Chen, D.Z.[Danny Z.], Wu, J.[Jian],
A Hierarchical Graph Network for 3D Object Detection on Point Clouds,
CVPR20(389-398)
IEEE DOI 2008
Shape, Semantics, Proposals, Object detection, Convolution, Feature extraction BibRef

Shen, X., Stamos, I.,
Frustum VoxNet for 3D object detection from RGB-D or Depth images,
WACV20(1687-1695)
IEEE DOI 2006
Object detection, Training, Robots, Proposals, Sensors BibRef

Tang, Y.S., Lee, G.H.,
Transferable Semi-Supervised 3D Object Detection From RGB-D Data,
ICCV19(1931-1940)
IEEE DOI 2004
image classification, image colour analysis, object detection, stereo image processing, supervised learning, Estimation BibRef

Lang, A.H.[Alex H.], Vora, S.[Sourabh], Caesar, H.[Holger], Zhou, L.[Lubing], Yang, J.[Jiong], Beijbom, O.[Oscar],
PointPillars: Fast Encoders for Object Detection From Point Clouds,
CVPR19(12689-12697).
IEEE DOI 2002
BibRef

Lin, W., Chen, Y., Wang, C., Li, J.,
Using Edgeconv to Improve 3d Object Detection From RGB-D Data,
Indoor3D19(835-839).
DOI Link 1912
BibRef

Yang, Z.T.[Ze-Tong], Sun, Y.N.[Ya-Nan], Liu, S.[Shu], Shen, X.Y.[Xiao-Yong], Jia, J.Y.[Jia-Ya],
STD: Sparse-to-Dense 3D Object Detector for Point Cloud,
ICCV19(1951-1960)
IEEE DOI 2004
computer graphics, feature extraction, image representation, neural nets, object detection, STD, point cloud, Training BibRef

Yang, B.[Bin], Luo, W.[Wenjie], Urtasun, R.[Raquel],
PIXOR: Real-time 3D Object Detection from Point Clouds,
CVPR18(7652-7660)
IEEE DOI 1812
Object detection, Detectors, Feature extraction, Real-time systems, Computer architecture BibRef

Zhou, Y., Tuzel, O.,
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection,
CVPR18(4490-4499)
IEEE DOI 1812
Laser radar, Feature extraction, Shape, Proposals, Encoding BibRef

Hu, N.[Nan], Ma, H.M.[Hui-Min], Le, C.[Chao], Shao, X.H.[Xue-Hui],
Multi-Modal Feature Fusion Network for Ghost Imaging Object Detection,
ICIP18(351-355)
IEEE DOI 1809
Only low resolution, depth data. Imaging, Feature extraction, Streaming media, Object detection, BibRef

Zheng, T., Chen, C., Yuan, J., Li, B., Ren, K.,
PointCloud Saliency Maps,
ICCV19(1598-1606)
IEEE DOI 2004
Code, Saliency.
WWW Link. convolutional neural nets, image classification, image representation, image segmentation, object detection, DGCNN, Predictive models BibRef

Zhang, Z., Hua, B., Yeung, S.,
ShellNet: Efficient Point Cloud Convolutional Neural Networks Using Concentric Shells Statistics,
ICCV19(1607-1616)
IEEE DOI 2004
convolutional neural nets, feature extraction, image classification, image representation, image segmentation, Semantics BibRef

Li, J.X.[Jia-Xin], Lee, G.H.[Gim Hee],
USIP: Unsupervised Stable Interest Point Detection From 3D Point Clouds,
ICCV19(361-370)
IEEE DOI 2004
Code, Interest Pointe.
WWW Link. feature extraction, learning (artificial intelligence), object detection, probability, Solid modeling BibRef

Yin, K., Liu, S., Liu, R., Chen, Y., Shen, K.,
Cross Modal Multiscale Fusion Net for Real-time RGB-D Detection,
ICPR18(2386-2391)
IEEE DOI 1812
convolution, feature extraction, feedforward neural nets, image colour analysis, object detection, sensor fusion, Merging BibRef

Qi, C.R., Liu, W., Wu, C., Su, H., Guibas, L.J.,
Frustum PointNets for 3D Object Detection from RGB-D Data,
CVPR18(918-927)
IEEE DOI 1812
Object detection, Proposals, Image segmentation, Detectors BibRef

Guo, L.[Lin], Fan, G.L.[Guo-Liang], Sheng, W.[Weihua],
Robust object detection by cuboid matching with local plane optimization in indoor RGB-D images,
VCIP17(1-4)
IEEE DOI 1804
geometry, image colour analysis, object detection, optimisation, cuboid candidates, cuboid initialization, indoor scene BibRef

Lahoud, J., Ghanem, B.,
2D-Driven 3D Object Detection in RGB-D Images,
ICCV17(4632-4640)
IEEE DOI 1802
image colour analysis, learning (artificial intelligence), multilayer perceptrons, object detection, search problems, BibRef

Audet, F.[François], Allili, M.S.[Mohand Said], Cretu, A.M.[Ana-Maria],
Salient Object Detection in Images by Combining Objectness Clues in the RGBD Space,
ICIAR17(247-255).
Springer DOI 1706
BibRef

Lev, J., Lim, J.H., Ouarti, N.,
Principal curvature of point cloud for 3D shape recognition,
ICIP17(610-614)
IEEE DOI 1803
Histograms, Noise measurement, Object recognition, Robustness, Sensors, Shape, Histograms, Principal curvature BibRef

Pang, G.[Guan], Neumann, U.[Ulrich],
3D point cloud object detection with multi-view convolutional neural network,
ICPR16(585-590)
IEEE DOI 1705
Complexity theory, Detectors, Object detection, Search problems, Training. 3D object extraction from point clouds. BibRef

Takabe, A., Takehara, H., Kawai, N., Sato, T., Machida, T., Nakanishi, S., Yokoya, N.,
Moving object detection from a point cloud using photometric and depth consistencies,
ICPR16(561-566)
IEEE DOI 1705
Cameras, Data models, Histograms, Measurement by laser beam, Object detection, Solid modeling, Three-dimensional, displays BibRef

Wang, S.T.[Song-Tao], Zhou, Z.[Zhen], Qu, H.B.[Han-Bing], Li, B.[Bin],
Visual Saliency Detection for RGB-D Images with Generative Model,
ACCV16(V: 20-35).
Springer DOI 1704
BibRef

Peng, H.[Houwen], Li, B.[Bing], Xiong, W.H.[Wei-Hua], Hu, W.M.[Wei-Ming], Ji, R.R.[Rong-Rong],
RGBD Salient Object Detection: A Benchmark and Algorithms,
ECCV14(III: 92-109).
Springer DOI 1408
BibRef

Ren, Z.[Zhile], Sudderth, E.B.[Erik B.],
3D Object Detection with Latent Support Surfaces,
CVPR18(937-946)
IEEE DOI 1812
BibRef
Earlier:
Three-Dimensional Object Detection and Layout Prediction Using Clouds of Oriented Gradients,
CVPR16(1525-1533)
IEEE DOI 1612
Object detection, Feature extraction, Solid modeling, Shape, Proposals BibRef

Shigematsu, R., Feng, D., You, S., Barnes, N.[Nick],
Learning RGB-D Salient Object Detection Using Background Enclosure, Depth Contrast, and Top-Down Features,
CogCV17(2749-2757)
IEEE DOI 1802
Computer architecture, Feature extraction, Histograms, Image color analysis, Microprocessors, Object detection, Visualization BibRef

Feng, D., Barnes, N., You, S.,
HOSO: Histogram of Surface Orientation for RGB-D Salient Object Detection,
DICTA17(1-8)
IEEE DOI 1804
computer vision, graph theory, image colour analysis, object detection, HOSO, KDF, RGB-D data, RGB-D saliency, BibRef

Feng, D., Barnes, N.[Nick], You, S., McCarthy, C.[Chris],
Local Background Enclosure for RGB-D Salient Object Detection,
CVPR16(2343-2350)
IEEE DOI 1612
BibRef

Chandra, S.[Siddhartha], Chrysos, G.G.[Grigorios G.], Kokkinos, I.[Iasonas],
Surface Based Object Detection in RGBD Images,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Liu, W.[Wei], Ji, R.R.[Rong-Rong], Li, S.[Shaozi],
Towards 3D object detection with bimodal deep Boltzmann machines over RGBD imagery,
CVPR15(3013-3021)
IEEE DOI 1510
BibRef

Song, S.[Shuran], Xiao, J.X.[Jian-Xiong],
Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images,
CVPR16(808-816)
IEEE DOI 1612
BibRef
Earlier:
Sliding Shapes for 3D Object Detection in Depth Images,
ECCV14(VI: 634-651).
Springer DOI 1408
BibRef

Knopp, J.[Jan], Prasad, M.[Mukta], Van Gool, L.J.[Luc J.],
Scene Cut: Class-Specific Object Detection and Segmentation in 3D Scenes,
3DIMPVT11(180-187).
IEEE DOI 1109
See also Orientation invariant 3D object classification using Hough transform based methods. BibRef

Monroy, A.[Antonio], Eigenstetter, A.[Angela], Ommer, B.[Bjorn],
Beyond straight lines: Object detection using curvature,
ICIP11(3561-3564).
IEEE DOI 1201
BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Range and Color, RGB-D Segmentation and Analysis .


Last update:Sep 14, 2020 at 15:32:18