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Feature extraction, Task analysis,
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Laser radar,
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Detectors, Object detection,
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Fuses, Saliency detection, Data models, Task analysis,
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Saliency detection, Bridges, Testing, Object detection,
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MLCVNet: Multi-Level Context VoteNet for 3D Object Detection,
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2008
Object detection, Feature extraction, Task analysis, Machine learning
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PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection,
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2008
Feature extraction, Proposals,
Encoding, Object detection, Aggregates
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Rünz, M.,
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Ma, L.,
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Lovegrove, S.,
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FroDO: From Detections to 3D Objects,
CVPR20(14708-14717)
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2008
Shape, Decoding, Image reconstruction,
Optimization, Simultaneous localization and mapping
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Najibi, M.,
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Kundu, A.,
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Fathi, A.,
DOPS: Learning to Detect 3D Objects and Predict Their 3D Shapes,
CVPR20(11910-11919)
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2008
Shape, Object detection,
Laser radar, Training, Pipelines
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Vora, S.,
Lang, A.H.,
Helou, B.,
Beijbom, O.,
PointPainting: Sequential Fusion for 3D Object Detection,
CVPR20(4603-4611)
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2008
Laser radar, Image segmentation,
Semantics, Object detection, Pipeline processing, Cameras
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Qi, C.R.,
Chen, X.,
Litany, O.,
Guibas, L.J.,
ImVoteNet: Boosting 3D Object Detection in Point Clouds With Image
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CVPR20(4403-4412)
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2008
Object detection, Proposals, Feature extraction, Poles and towers, Semantics
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Peng, W.,
Pan, H.,
Liu, H.,
Sun, Y.,
IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision
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CVPR20(13012-13021)
IEEE DOI
2008
Object detection, Laser radar,
Estimation, Cameras, Stereo vision
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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
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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
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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
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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
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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
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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
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Shi, W.,
Rajkumar, R.,
Point-GNN: Graph Neural Network for 3D Object Detection in a Point
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CVPR20(1708-1716)
IEEE DOI
2008
Neural networks, Object detection,
Feature extraction, Convolution, Laser radar, Shape
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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
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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
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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
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Vora, S.[Sourabh],
Caesar, H.[Holger],
Zhou, L.[Lubing],
Yang, J.[Jiong],
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PointPillars: Fast Encoders for Object Detection From Point Clouds,
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IEEE DOI
2002
BibRef
Lin, W.,
Chen, Y.,
Wang, C.,
Li, J.,
Using Edgeconv to Improve 3d Object Detection From RGB-D Data,
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DOI Link
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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
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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
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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
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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
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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
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Li, J.X.[Jia-Xin],
Lee, G.H.[Gim Hee],
USIP: Unsupervised Stable Interest Point Detection From 3D Point
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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
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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,
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Audet, F.[François],
Allili, M.S.[Mohand Said],
Cretu, A.M.[Ana-Maria],
Salient Object Detection in Images by Combining Objectness Clues in the
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ICIAR17(247-255).
Springer DOI
1706
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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
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Pang, G.[Guan],
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3D point cloud object detection with multi-view convolutional neural
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ICPR16(585-590)
IEEE DOI
1705
Complexity theory, Detectors, Object detection, Search problems,
Training.
3D object extraction from point clouds.
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Takabe, A.,
Takehara, H.,
Kawai, N.,
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Machida, T.,
Nakanishi, S.,
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Moving object detection from a point cloud using photometric and
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ICPR16(561-566)
IEEE DOI
1705
Cameras, Data models, Histograms, Measurement by laser beam,
Object detection, Solid modeling, Three-dimensional, displays
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Wang, S.T.[Song-Tao],
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Visual Saliency Detection for RGB-D Images with Generative Model,
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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 .