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A key technical challenge in performing 6D object pose estimation from RGB-D image is to fully leverage the two complementary data sources.
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“Are we ready for autonomous driving? the kitti vision benchmark suite”
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Shuran Song and Jianxiong Xiao · 2014
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“Latent-class hough forests for 3D object detection and pose estimation”
Alykhan Tejani, Danhang Tang, Rigas Kouskouridas and Tae-Kyun Kim · 2014
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“Single image 3D object detection and pose estimation for grasping”
Menglong Zhu et al · 2014
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Berk Calli et al · 2015
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Max Schwarz, Hannes Schulz and Sven Behnke · 2015
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“Viewpoints and keypoints”
Shubham Tulsiani and Jitendra Malik · 2015
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“Learning descriptors for object recognition and 3d pose estimation”
Paul Wohlhart and Vincent Lepetit · 2015
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“Deep learning of local rgb-d patches for 3d object detection and 6d pose estimation”
Wadim Kehl et al · 2016
“6-dof object pose from semantic keypoints”
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Charles Qi et al · 2017
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“Subcategory-aware convolutional neural networks for object proposals and detection”
Yu Xiang, Wongun Choi, Yuanqing Lin and Silvio Savarese · 2017
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“Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes”
Yu Xiang, Tanner Schmidt, Venkatraman Narayanan and Dieter Fox · 2017
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“Pointfusion: Deep sensor fusion for 3d bounding box estimation”
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“Pose estimation for augmented reality: a hands-on survey”
Eric Marchand, Hideaki Uchiyama and Fabien Spindler · 2016
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“Project Tango”
Eitan Marder-Eppstein · 2016
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“Pointnet: Deep learning on point sets for 3d classification and segmentation”
Charles Qi, Hao Su, Kaichun Mo and Leonidas Guibas · 2016
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“Deep sliding shapes for amodal 3D object detection in RGB-D images”
Shuran Song and Jianxiong Xiao · 2016
Cited alongside, same era.
“Rotational Subgroup Voting and Pose Clustering for Robust 3D Object Recognition”
Anders Buch, Lilita Kiforenko and Dirk Kraft · 2017
Cited alongside, same era.
“Multi-View 3D Object Detection Network for Autonomous Driving”
Xiaozhi Chen et al · 2017
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Danfei Xu, Dragomir Anguelov and Ashesh Jain · 2017
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“Voxelnet: End-to-end learning for point cloud based 3d object detection”
Yin Zhou and Oncel Tuzel · 2017
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“A Unified Framework for Multi-View Multi-Class Object Pose Estimation”
Chi Li, Jin Bai and Gregory Hager · 2018
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“DeepIM: Deep Iterative Matching for 6D Pose Estimation”
Yi Li et al · 2018
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“Implicit 3D Orientation Learning for 6D Object Detection from RGB Images”
Martin Sundermeyer et al · 2018
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“Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning”
Supasorn Suwajanakorn, Noah Snavely, Jonathan Tompson and Mohammad Norouzi · 2018
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“Real-Time Seamless Single Shot 6D Object Pose Prediction”
Bugra Tekin, Sudipta. Sinha and Pascal Fua · 2018
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“Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects”
Jonathan Tremblay et al · 2018
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“6D pose estimation using an improved method based on point pair features”
Joel Vidal, Chyi-Yeu Lin and Robert Mart“’ · 2018
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“Discriminatively trained templates for 3d object detection: A real time scalable approach”
Reyes Rios-Cabrera and Tinne Tuytelaars · 2055
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