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Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality.
Structural indexing: efficient 3-d object recognition
F. Stein and G. Medioni · 1992
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Point signatures: A new representation for 3d object recognition
C. S. Chua and R. Jarvis · 1997
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A. E. Johnson and M. Hebert · 1999
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Development of small robot for home floor cleaning
Y.-J. Oh and Y. Watanabe · 2002
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Multiple 3d object tracking for augmented reality
Y. Park, V. Lepetit, and W. Woo · 2008
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Fast point feature histograms (fpfh) for 3d registration
R. B. Rusu, N. Blodow, and M. Beetz · 2009
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Scale-hierarchical 3d object recognition in cluttered scenes
P. Bariya and K. Nishino · 2010
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On the repeatability and quality of keypoints for local feature-based 3d object retrieval from cluttered scenes
A. Mian, M. Bennamoun, and R. Owens · 2010
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Depth Kernel Descriptors for Object Recognition
L. Bo, X. Ren, and D. Fox · 2011
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A multilevel mixture-of-experts framework for pedestrian classification
M. Enzweiler and D. M. Gavrila · 2011
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Real-time human pose recognition in parts from single depth images
J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake · 2011
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Voting-based pose estimation for robotic assembly using a 3d sensor
C. Choi, Y. Taguchi, O. Tuzel, M. Y. Liu, and S. Ramalingam · 2012
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Are we ready for autonomous driving? the kitti vision benchmark suite
A. Geiger, P. Lenz, and R. Urtasun · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Some improvements on deep convolutional neural network based image classification
A. G. Howard · 2013
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Detailed 3d representations for object recognition and modeling
M. Z. Zia, M. Stark, B. Schiele, and K. Schindler · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Pedestrian detection combining RGB and dense LIDAR data
C. Premebida, J. Carreira, J. Batista, and U. Nunes · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Monocular 3d object detection for autonomous driving
X. Chen, K. Kundu, Z. Zhang, H. Ma, S. Fidler, and R. Urtasun · 2016
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Pl-svo: Semi-direct monocular visual odometry by combining points and line segments
R. Gomez-Ojeda, J. Briales, and J. Gonzalez-Jimenez · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Vehicle detection from 3d lidar using fully convolutional network
B. Li, T. Zhang, and T. Xia · 2016
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Ssd: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg · 2016
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Deep Sliding Shapes for amodal 3D object detection in RGB-D images
S. Song and J. Xiao · 2016
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Sliding shapes for 3d object detection in depth images
S. Song and J. Xiao · 2014
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Learning to rank 3d features
O. Tuzel, M.-Y. Liu, Y. Taguchi, and A. Raghunathan · 2014
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Are cars just 3d boxes? jointly estimating the 3d shape of multiple objects
M. Z. Zia, M. Stark, and K. Schindler · 2014
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3d object proposals for accurate object class detection
X. Chen, K. Kundu, Y. Zhu, A. Berneshawi, H. Ma, S. Fidler, and R. Urtasun · 2015
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Fast r-cnn
R. Girshick · 2015
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Multiview random forest of local experts combining rgb and lidar data for pedestrian detection
A. Gonzalez, G. Villalonga, J. Xu, D. Vazquez, J. Amores, and A. Lopez · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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Multi-view 3d object detection network for autonomous driving
X. Chen, H. Ma, J. Wan, B. Li, and T. Xia · 2017
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Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks
M. Engelcke, D. Rao, D. Z. Wang, C. H. Tong, and I. Posner · 2017
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On-board object detection: Multicue, multimodal, and multiview random forest of local experts
A. González, D. Vázquez, A. M. López, and J. Amores · 2017
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3d fully convolutional network for vehicle detection in point cloud
B. Li · 2017
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Focal loss for dense object detection
T. Lin, P. Goyal, R. B. Girshick, K. He, and P. Dollár · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
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YOLO9000: better, faster, stronger
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