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Satellite pose detection
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Range between anchors and sensors on the body.
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Shen, Y.Q.[Yue-Qian],
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Extracting Individual Bricks from a Laser Scan Point Cloud of an
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Point cloud, Feature descriptor, Bin-picking
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2008
RGB-D data.
Pose estimation, Quaternions,
Object recognition, Artificial neural networks, Search problems,
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Papaioannidis, C.[Christos],
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2010
Pose estimation, Feature extraction,
Training, Task analysis, Training data,
synthetic data
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Guo, J.W.[Jian-Wei],
Xing, X.J.[Xue-Jun],
Quan, W.[Weize],
Yan, D.M.[Dong-Ming],
Gu, Q.Y.[Qing-Yi],
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Zhang, X.P.[Xiao-Peng],
Efficient Center Voting for Object Detection and 6D Pose Estimation
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IP(30), 2021, pp. 5072-5084.
IEEE DOI
2106
Pose estimation, Shape,
Object detection, Feature extraction, Object recognition,
3D point cloud
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Li, J.[Jie],
Zhuang, Y.Q.[Yi-Qi],
Peng, Q.[Qi],
Zhao, L.[Liang],
Pose Estimation of Non-Cooperative Space Targets Based on
Cross-Source Point Cloud Fusion,
RS(13), No. 21, 2021, pp. xx-yy.
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Sun, D.Q.[Dian-Qi],
Hu, L.[Liang],
Duan, H.X.[Hui-Xian],
Pei, H.D.[Hao-Dong],
Relative Pose Estimation of Non-Cooperative Space Targets Using a TOF
Camera,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link
2212
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Yang, C.X.[Chen-Xi],
Zhou, Z.B.[Zhi-Bo],
Zhuang, H.Y.[Han-Yang],
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Yang, M.[Ming],
Global Pose Initialization Based on Gridded Gaussian Distribution
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ITS(24), No. 5, May 2023, pp. 5094-5104.
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2305
Point cloud compression, Gaussian distribution, Task analysis,
Location awareness, Pose estimation, Laser radar, indoor scenarios
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Zou, L.[Lu],
Huang, Z.J.[Zhang-Jin],
Gu, N.[Naijie],
Wang, G.P.[Guo-Ping],
Learning geometric consistency and discrepancy for category-level 6D
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PR(145), 2024, pp. 109896.
Elsevier DOI
2311
6D object pose estimation, 3D object detection,
Point cloud processing, Shape recovery
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Li, Y.J.[Yu-Jie],
Yin, Z.Y.[Zhi-Yun],
Zheng, Y.C.[Yu-Chao],
Lu, H.M.[Hui-Min],
Kamiya, T.[Tohru],
Nakatoh, Y.[Yoshihisa],
Serikawa, S.[Seiichi],
Pose Estimation of Point Sets Using Residual MLP in Intelligent
Transportation Infrastructure,
ITS(24), No. 11, November 2023, pp. 13359-13369.
IEEE DOI
2311
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Thalhammer, S.[Stefan],
Weibel, J.B.[Jean-Baptiste],
Vincze, M.[Markus],
Garcia-Rodriguez, J.[Jose],
Self-supervised Vision Transformers for 3D pose estimation of novel
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IVC(139), 2023, pp. 104816.
Elsevier DOI
2311
Object pose estimation, Template matching, Vision transformer,
Self-supervised learning
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Ye, R.[Ruida],
Ren, Y.[Yuan],
Zhu, X.Y.[Xiang-Yang],
Wang, Y.J.[Yu-Jing],
Liu, M.Y.[Ming-Yue],
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An Efficient Pose Estimation Algorithm for Non-Cooperative Space
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Wang, G.P.[Guo-Ping],
GPT-COPE: A Graph-Guided Point Transformer for Category-Level Object
Pose Estimation,
CirSysVideo(34), No. 4, April 2024, pp. 2385-2398.
IEEE DOI
2404
Shape, Point cloud compression, Pose estimation,
Feature extraction, Solid modeling, vision transformer
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Zhang, Y.[Yan],
Zhang, L.[Lu],
Zhao, X.[Xin],
Fu, H.Y.[Hong-Yong],
Yu, D.[Dequan],
Automatic Point Cloud Registration for 3D Virtual-to-Real
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IEEE DOI
2404
Point cloud compression, Solid modeling,
Feature extraction, Data models, virtual-to-real
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Zhan, Y.[Yue],
Wang, X.[Xin],
Nie, L.[Lang],
Zhao, Y.[Yang],
Yang, T.[Tangwen],
Ruan, Q.Q.[Qiu-Qi],
TG-Pose: Delving Into Topology and Geometry for Category-Level Object
Pose Estimation,
MultMed(26), 2024, pp. 9749-9762.
IEEE DOI
2410
Pose estimation, Point cloud compression, Shape,
Feature extraction, Solid modeling, Task analysis, Geometry,
persistent homology
BibRef
You, Y.[Yang],
He, W.H.[Wen-Hao],
Liu, J.[Jin],
Xiong, H.K.[Hong-Kai],
Wang, W.M.[Wei-Ming],
Lu, C.[Cewu],
CPPF++: Uncertainty-Aware Sim2Real Object Pose Estimation by Vote
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PAMI(46), No. 12, December 2024, pp. 9239-9254.
IEEE DOI
2411
Pose estimation, Training, Solid modeling, Noise measurement,
Uncertainty, Training data, Filtering, Object pose estimation,
dataset creation
BibRef
Xu, C.[Chao],
Li, A.[Ang],
Chen, L.H.[Ling-Hao],
Liu, Y.L.[Yu-Lin],
Shi, R.X.[Ruo-Xi],
Su, H.[Hao],
Liu, M.H.[Ming-Hua],
SPARP: Fast 3d Object Reconstruction and Pose Estimation from Sparse
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ECCV24(LXIV: 143-163).
Springer DOI
2412
BibRef
Hou, P.H.[Pi-Hong],
Zhang, Y.F.[Yong-Fang],
Wu, Y.[Yi],
Yan, P.Y.[Peng-Yu],
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FormerPose: An efficient multi-scale fusion Transformer network based
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JVCIR(106), 2025, pp. 104346.
Elsevier DOI
2501
6D pose estimation, Holistic method, Multi-modal Transformer,
Multi-scale fusion, Robot grasping
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Dai, Y.[Yue],
Ying, S.H.[Shi-Hui],
Gao, Y.[Yue],
Exploring Local and Global Consistent Correlation on Hypergraph for
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IEEE DOI
2501
Point cloud compression, Correlation,
Principal component analysis, Representation learning,
cross-attention
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Vutukur, S.R.[Shishir Reddy],
Haugaard, R.L.[Rasmus Laurvig],
Huang, J.W.[Jun-Wen],
Busam, B.[Benjamin],
Birdal, T.[Tolga],
Alignist: CAD-Informed Orientation Distribution Estimation by Fusing
Shape and Correspondences,
ECCV24(II: 351-369).
Springer DOI
2412
BibRef
Zhang, L.[Li],
Meng, W.Q.[Wei-Qing],
Zhong, Y.[Yan],
Kong, B.[Bin],
Xu, M.L.[Ming-Liang],
Du, J.M.[Jian-Ming],
Wang, X.[Xue],
Wang, R.[Rujing],
Liu, L.[Liu],
U-cope: Taking a Further Step to Universal 9d Category-level Object
Pose Estimation,
ECCV24(X: 254-270).
Springer DOI
2412
BibRef
Liang, Y.[Yujia],
Ye, Z.X.[Zi-Xuan],
Liu, W.Z.[Wen-Ze],
Lu, H.[Hao],
Scape: A Simple and Strong Category-agnostic Pose Estimator,
ECCV24(XXIII: 478-494).
Springer DOI
2412
BibRef
Zhang, R.[Ruida],
Huang, Z.Q.[Zi-Qin],
Wang, G.[Gu],
Zhang, C.Y.G.[Chen-Yang-Guang],
Di, Y.[Yan],
Zuo, X.X.[Xing-Xing],
Tang, J.W.[Ji-Wen],
Ji, X.Y.[Xiang-Yang],
Lapose: Laplacian Mixture Shape Modeling for RGB-based Category-level
Object Pose Estimation,
ECCV24(XXV: 467-484).
Springer DOI
2412
BibRef
Örnek, E.P.[Evin Pinar],
Labbé, Y.[Yann],
Tekin, B.[Bugra],
Ma, L.[Lingni],
Keskin, C.[Cem],
Forster, C.[Christian],
Hodan, T.[Tomas],
Foundpose: Unseen Object Pose Estimation with Foundation Features,
ECCV24(XXVI: 163-182).
Springer DOI
2412
BibRef
Liu, B.[Bowen],
Liu, W.[Wei],
Chen, S.[Siang],
Xie, P.W.[Peng-Wei],
Wang, G.J.[Gui-Jin],
Category-Agnostic Pose Estimation for Point Clouds,
ICIP24(3533-3539)
IEEE DOI
2411
Point cloud compression, Training, Annotations, Pose estimation,
Feature extraction, Task analysis, category-agnostic,
pose estimation
BibRef
Mallis, D.[Dimitrios],
Ali, S.A.[Sk Aziz],
Dupont, E.[Elona],
Cherenkova, K.[Kseniya],
Karadeniz, A.S.[Ahmet Serdar],
Khan, M.S.[Mohammad Sadil],
Kacem, A.[Anis],
Gusev, G.[Gleb],
Aouada, D.[Djamila],
SHARP Challenge 2023: Solving CAD History and pArameters Recovery
from Point clouds and 3D scans. Overview, Datasets, Metrics, and
Baselines,
SHARP23(1778-1787)
IEEE DOI
2401
BibRef
Manousis, T.[Theodoros],
Passalis, N.[Nikolaos],
Tefas, A.[Anastasios],
Enabling High-Resolution Pose Estimation in Real Time Using Active
Perception,
ICIP23(2425-2429)
IEEE DOI
2312
BibRef
Hodan, T.[Tomas],
Sundermeyer, M.[Martin],
Labbé, Y.[Yann],
Nguyen, V.N.[Van Nguyen],
Wang, G.[Gu],
Brachmann, E.[Eric],
Drost, B.[Bertram],
Lepetit, V.[Vincent],
Rother, C.[Carsten],
Matas, J.[Jiri],
BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of
Seen and Unseen Rigid Objects,
CV4MR24(5610-5619)
IEEE DOI
2410
Location awareness, Training, Solid modeling, Accuracy,
Pose estimation, Real-time systems, object pose estimation, unseen objects
BibRef
Sundermeyer, M.[Martin],
Hodan, T.[Tomá],
Labbé, Y.[Yann],
Wang, G.[Gu],
Brachmann, E.[Eric],
Drost, B.[Bertram],
Rother, C.[Carsten],
Matas, J.G.[Jirí G.],
BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of
Specific Rigid Objects,
CV4MR23(2785-2794)
IEEE DOI
2309
BibRef
Wang, S.[Sijie],
Kang, Q.Y.[Qi-Yu],
She, R.[Rui],
Wang, W.[Wei],
Zhao, K.[Kai],
Song, Y.[Yang],
Tay, W.P.[Wee Peng],
HypLiLoc: Towards Effective LiDAR Pose Regression with Hyperbolic
Fusion,
CVPR23(5176-5185)
IEEE DOI
2309
WWW Link.
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Kadam, P.[Pranav],
Zhou, Q.Y.[Qing-Yang],
Liu, S.[Shan],
Kuo, C.C.J.[C.C. Jay],
PCRP: Unsupervised Point Cloud Object Retrieval and Pose Estimation,
ICIP22(1596-1600)
IEEE DOI
2211
Point cloud compression, Representation learning,
Learning systems, Pose estimation, Feature extraction, Registers,
successive subspace learning
BibRef
Tian, L.[Long],
Cavallaro, A.[Andrea],
Oh, C.[Changjae],
Cluster-Based 3D Keypoint Detection for Category-Agnostic 6D Pose
Tracking,
ICIP22(3651-3655)
IEEE DOI
2211
Point cloud compression, Solid modeling, Target tracking,
Image coding, Annotations, Pose estimation, 6D pose tracking, category-agnostic
BibRef
Sajnani, R.[Rahul],
Poulenard, A.[Adrien],
Jain, J.[Jivitesh],
Dua, R.[Radhika],
Guibas, L.J.[Leonidas J.],
Sridhar, S.[Srinath],
ConDor:
Self-Supervised Canonicalization of 3D Pose for Partial Shapes,
CVPR22(16948-16958)
IEEE DOI
2210
Point cloud compression, Measurement, Training, Tensors,
Image analysis, Shape, Scene analysis and understanding,
Self- semi- meta- unsupervised learning
BibRef
Lee, T.[Taeyeop],
Tremblay, J.[Jonathan],
Blukis, V.[Valts],
Wen, B.[Bowen],
Lee, B.U.[Byeong-Uk],
Shin, I.[Inkyu],
Birchfield, S.[Stan],
Kweon, I.S.[In So],
Yoon, K.J.[Kuk-Jin],
TTA-COPE: Test-Time Adaptation for Category-Level Object Pose
Estimation,
CVPR23(21285-21295)
IEEE DOI
2309
BibRef
Lee, T.[Taeyeop],
Lee, B.U.[Byeong-Uk],
Shin, I.[Inkyu],
Choe, J.[Jaesung],
Shin, U.[Ukcheol],
Kweon, I.S.[In So],
Yoon, K.J.[Kuk-Jin],
UDA-COPE: Unsupervised Domain Adaptation for Category-level Object
Pose Estimation,
CVPR22(14871-14880)
IEEE DOI
2210
Training, Point cloud compression, Solid modeling, Filtering,
Pose estimation, Pipelines, Self-supervised learning, Robot vision,
Vision applications and systems
BibRef
Di, Y.[Yan],
Zhang, R.[Ruida],
Lou, Z.Q.[Zhi-Qiang],
Manhardt, F.[Fabian],
Ji, X.Y.[Xiang-Yang],
Navab, N.[Nassir],
Tombari, F.[Federico],
GPV-Pose: Category-level Object Pose Estimation via Geometry-guided
Point-wise Voting,
CVPR22(6771-6781)
IEEE DOI
2210
Point cloud compression, Measurement, Shape, Pose estimation,
Real-time systems, Pose estimation and tracking,
Scene analysis and understanding
BibRef
Sun, J.M.[Jia-Ming],
Wang, Z.[Zihao],
Zhang, S.[Siyu],
He, X.Y.[Xing-Yi],
Zhao, H.C.[Hong-Cheng],
Zhang, G.F.[Guo-Feng],
Zhou, X.W.[Xiao-Wei],
OnePose: One-Shot Object Pose Estimation without CAD Models,
CVPR22(6815-6824)
IEEE DOI
2210
Training, Location awareness, Solid modeling, Visualization, Runtime,
Pose estimation, Pose estimation and tracking,
Vision applications and systems
BibRef
Shugurov, I.[Ivan],
Li, F.[Fu],
Busam, B.[Benjamin],
Ilic, S.[Slobodan],
OSOP: A Multi-Stage One Shot Object Pose Estimation Framework,
CVPR22(6825-6834)
IEEE DOI
2210
Training, Solid modeling, Computational modeling, Pose estimation,
Training data, Object detection, Pose estimation and tracking,
Transfer/low-shot/long-tail learning
BibRef
Musallam, M.A.[Mohamed Adel],
Gaudilličre, V.[Vincent],
del Castillo, M.O.[Miguel Ortiz],
Al Ismaeil, K.[Kassem],
Aouada, D.[Djamila],
Leveraging Equivariant Features for Absolute Pose Regression,
CVPR22(6866-6876)
IEEE DOI
2210
Computational modeling, Pose estimation, Training data,
Feature extraction, Cameras, Convolutional neural networks, Robot vision
BibRef
Nguyen, V.N.[Van Nguyen],
Hu, Y.L.[Yin-Lin],
Xiao, Y.[Yang],
Salzmann, M.[Mathieu],
Lepetit, V.[Vincent],
Templates for 3D Object Pose Estimation Revisited: Generalization to
New Objects and Robustness to Occlusions,
CVPR22(6761-6770)
IEEE DOI
2210
Training, Solid modeling, Image recognition, Impedance matching,
Pose estimation, Pose estimation and tracking, Robot vision
BibRef
Zhao, C.[Chen],
Ge, Y.X.[Yi-Xiao],
Zhu, F.[Feng],
Zhao, R.[Rui],
Li, H.S.[Hong-Sheng],
Salzmann, M.[Mathieu],
Progressive Correspondence Pruning by Consensus Learning,
ICCV21(6444-6453)
IEEE DOI
2203
Location awareness, Learning systems,
Computer network reliability, Stacking, Pose estimation, Fitting,
BibRef
Yang, H.[Heng],
Doran, C.[Chris],
Slotine, J.J.[Jean-Jacques],
Dynamical Pose Estimation,
ICCV21(5906-5915)
IEEE DOI
2203
Point cloud compression, Damping, Heuristic algorithms,
Pose estimation, Graphics processing units, Stereo,
Vision for robotics and autonomous vehicles
BibRef
Li, K.[Ke],
Wang, S.J.[Shi-Jie],
Zhang, X.[Xiang],
Xu, Y.F.[Yi-Fan],
Xu, W.J.[Wei-Jian],
Tu, Z.W.[Zhuo-Wen],
Pose Recognition with Cascade Transformers,
CVPR21(1944-1953)
IEEE DOI
2111
Heating systems, Visualization, Transformers,
Pattern recognition, Decoding, Task analysis
BibRef
Fischer, K.[Kai],
Simon, M.[Martin],
Milz, S.[Stefan],
Mäder, P.[Patrick],
StickyLocalization: Robust End-To-End Relocalization on Point Clouds
using Graph Neural Networks,
WACV22(307-316)
IEEE DOI
2202
Point cloud compression, Training, Runtime,
Refining, Pose estimation, Deep Learning
BibRef
Fischer, K.[Kai],
Simon, M.[Martin],
Ölsner, F.[Florian],
Milz, S.[Stefan],
Groß, H.M.[Horst-Michael],
Mäder, P.[Patrick],
StickyPillars: Robust and Efficient Feature Matching on Point Clouds
using Graph Neural Networks,
CVPR21(313-323)
IEEE DOI
2111
Deep learning, Runtime, Laser radar,
Pose estimation, Pipelines, Transformers
BibRef
Müller, N.[Nikolas],
Stenzel, J.[Jonas],
Chen, J.J.[Jian-Jia],
Self-supervised Detection and Pose Estimation of Logistical Objects
in 3D Sensor Data,
ICPR21(10251-10258)
IEEE DOI
2105
Location awareness, Solid modeling,
Pose estimation, Robot vision systems, Training data,
learning-based vision
BibRef
Tatemichi, H.[Hiroki],
Kawanishi, Y.[Yasutomo],
Deguchi, D.[Daisuke],
Ide, I.[Ichiro],
Amma, A.[Ayako],
Murase, H.[Hiroshi],
Median-Shape Representation Learning for Category-Level Object Pose
Estimation in Cluttered Environments,
ICPR21(4473-4480)
IEEE DOI
2105
Pose estimation of an unknown object instance in an object category
from a depth image.
Training, Shape, Pose estimation,
Feature extraction, Image reconstruction
BibRef
Grabner, A.[Alexander],
Wang, Y.M.[Ya-Ming],
Zhang, P.Z.[Pei-Zhao],
Guo, P.H.[Pei-Hong],
Xiao, T.[Tong],
Vajda, P.[Peter],
Roth, P.M.[Peter M.],
Lepetit, V.[Vincent],
Geometric Correspondence Fields: Learned Differentiable Rendering for
3d Pose Refinement in the Wild,
ECCV20(XVI: 102-119).
Springer DOI
2010
BibRef
Tong, X.W.[Xun-Wei],
Li, R.F.[Rui-Feng],
Ge, L.Z.[Lian-Zheng],
Zhao, L.J.[Li-Jun],
Wang, K.[Ke],
Pose Refinement of Occluded 3D Objects Based on Visible Surface
Extraction,
ICIVC20(176-181)
IEEE DOI
2009
Iterative closest point algorithm,
Surface treatment, Pose estimation, Robustness, Cameras, scene occlusion
BibRef
Wang, J.S.[Jia-Shun],
Wen, C.[Chao],
Fu, Y.W.[Yan-Wei],
Lin, H.T.[Hai-Tao],
Zou, T.Y.[Tian-Yun],
Xue, X.Y.[Xiang-Yang],
Zhang, Y.D.[Yin-Da],
Neural Pose Transfer by Spatially Adaptive Instance Normalization,
CVPR20(5830-5838)
IEEE DOI
2008
Code, Mesh Pose.
WWW Link. Shape, Feature extraction, Strain,
Decoding, Machine learning, Task analysis
BibRef
Yang, Z.P.[Zhen-Pei],
Yan, S.M.[Si-Ming],
Huang, Q.X.[Qi-Xing],
Extreme Relative Pose Network Under Hybrid Representations,
CVPR20(2452-2461)
IEEE DOI
2008
Feature extraction, Pose estimation, Robustness, Layout, Pipelines
BibRef
Liu, X.F.[Xiao-Feng],
Zou, Y.[Yang],
Che, T.[Tong],
Jia, P.[Ping],
Ding, P.[Peng],
You, J.[Jane],
Kumar, B.V.K.V.[B.V.K. Vijaya],
Conservative Wasserstein Training for Pose Estimation,
ICCV19(8261-8271)
IEEE DOI
2004
head, body, vehicle and 3D object pose.
entropy, learning (artificial intelligence),
object detection, optimisation, pose estimation,
BibRef
Yang, Z.P.[Zhen-Pei],
Pan, J.Z.[Jeffrey Z.],
Luo, L.J.[Lin-Jie],
Zhou, X.W.[Xiao-Wei],
Grauman, K.[Kristen],
Huang, Q.X.[Qi-Xing],
Extreme Relative Pose Estimation for RGB-D Scans via Scene Completion,
CVPR19(4526-4535).
IEEE DOI
2002
BibRef
Rasmussen, F.N.[Frederik Nřrby],
Andersen, S.T.[Sebastian Terp],
Grossmann, B.[Bjarne],
Boukas, E.[Evangelos],
Nalpantidis, L.[Lazaros],
Planar Pose Estimation Using Object Detection and Reinforcement
Learning,
CVS19(353-365).
Springer DOI
1912
BibRef
Alexandrov, S.V.[Sergey V.],
Patten, T.[Timothy],
Vincze, M.[Markus],
Leveraging Symmetries to Improve Object Detection and Pose Estimation
from Range Data,
CVS19(397-407).
Springer DOI
1912
BibRef
Thalhammer, S.,
Patten, T.[Timothy],
Vincze, M.[Markus],
SyDPose: Object Detection and Pose Estimation in Cluttered Real-World
Depth Images Trained using Only Synthetic Data,
3DV19(106-115)
IEEE DOI
1911
Pose estimation, Training,
Task analysis, Deep learning, Solid modeling,
depth data
BibRef
Gao, G.[Ge],
Lauri, M.[Mikko],
Zhang, J.W.[Jian-Wei],
Frintrop, S.[Simone],
Occlusion Resistant Object Rotation Regression from Point Cloud
Segments,
4DPose18(I:716-729).
Springer DOI
1905
BibRef
Wang, Y.M.[Ya-Ming],
Tan, X.[Xiao],
Yang, Y.[Yi],
Li, Z.,
Liu, X.,
Zhou, F.,
Davis, L.S.,
A Refined 3D Pose Dataset for Fine-Grained Object Categories,
R6D19(2797-2806)
IEEE DOI
2004
Dataset, Object Recognition.
HTML Version. image segmentation, object recognition, pose estimation,
statistical analysis, image segmentation networks, IoU,
Fine grained objects
BibRef
Wang, Y.M.[Ya-Ming],
Tan, X.[Xiao],
Yang, Y.[Yi],
Liu, X.[Xiao],
Ding, E.[Errui],
Zhou, F.[Feng],
Davis, L.S.[Larry S.],
3D Pose Estimation for Fine-Grained Object Categories,
4DPose18(I:619-632).
Springer DOI
1905
BibRef
Mahendran, S.[Siddharth],
Ali, H.[Haider],
Vidal, R.[René],
Convolutional Networks for Object Category and 3D Pose Estimation from
2D Images,
4DPose18(I:698-715).
Springer DOI
1905
BibRef
g
Poier, G.[Georg],
Opitz, M.[Michael],
Schinagl, D.[David],
Bischof, H.[Horst],
MURAUER: Mapping Unlabeled Real Data for Label AUstERity,
WACV19(1393-1402)
IEEE DOI
1904
learning (artificial intelligence), pose estimation,
mapping unlabeled real data for label austerity, MURAUER,
Neural networks
BibRef
He, X.W.[Xin-Wei],
Zhou, Y.[Yang],
Zhou, Z.C.[Zhi-Chao],
Bai, S.[Song],
Bai, X.[Xiang],
Triplet-Center Loss for Multi-view 3D Object Retrieval,
CVPR18(1945-1954)
IEEE DOI
1812
Shape, Solid modeling, Feature extraction, Benchmark testing, Task analysis
BibRef
Rosa, S.[Stefano],
Toscana, G.[Giorgio],
Fast Feature-Less Quaternion-based Particle Swarm Optimization for
Object Pose Estimation From RGB-D Images,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Jafari, O.H.[Omid Hosseini],
Mustikovela, S.K.[Siva Karthik],
Pertsch, K.[Karl],
Brachmann, E.[Eric],
Rother, C.[Carsten],
iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects,
ACCV18(III:477-492).
Springer DOI
1906
BibRef
Lin, M.,
Lin, L.,
Liang, X.,
Wang, K.,
Cheng, H.,
Recurrent 3D Pose Sequence Machines,
CVPR17(5543-5552)
IEEE DOI
1711
Feature extraction, Geometry, Image sequences, Pose estimation,
Solid modeling,
BibRef
Mousavian, A.,
Anguelov, D.,
Flynn, J.,
Koecká, J.,
3D Bounding Box Estimation Using Deep Learning and Geometry,
CVPR17(5632-5640)
IEEE DOI
1711
Object detection, Pose estimation, Shape, Solid modeling
BibRef
Rink, C.[Christian],
Kriegel, S.[Simon],
Streaming Monte Carlo Pose Estimation for Autonomous Object Modeling,
CRV16(156-163)
IEEE DOI
1612
3D modeling; Active sensing; Laser scanning; Pose estimation
BibRef
Zamir, A.R.[Amir R.],
Wekel, T.[Tilman],
Agrawal, P.[Pulkit],
Wei, C.[Colin],
Malik, J.[Jitendra],
Savarese, S.[Silvio],
Generic 3D Representation via Pose Estimation and Matching,
ECCV16(III: 535-553).
Springer DOI
1611
BibRef
Srinivasan, R.R.[Ranga Ramanujam],
Xia, Z.Y.[Zheng-Yu],
Kim, J.[Joohee],
Park, Y.S.[Young Soo],
Confidence indicators based pose estimation for high-quality 3D
reconstruction using depth image,
VCIP15(1-4)
IEEE DOI
1605
Anisotropic magnetoresistance
BibRef
Papon, J.[Jeremie],
Schoeler, M.[Markus],
Semantic Pose Using Deep Networks Trained on Synthetic RGB-D,
ICCV15(774-782)
IEEE DOI
1602
Furniture, indoor.
Adaptation models
BibRef
Mottaghi, R.[Roozbeh],
Xiang, Y.[Yu],
Savarese, S.[Silvio],
A coarse-to-fine model for 3D pose estimation and sub-category
recognition,
CVPR15(418-426)
IEEE DOI
1510
BibRef
Zach, C.[Christopher],
Penate-Sanchez, A.[Adrian],
Pham, M.T.[Minh-Tri],
A dynamic programming approach for fast and robust object pose
recognition from range images,
CVPR15(196-203)
IEEE DOI
1510
BibRef
Großmann, B.[Bjarne],
Siam, M.[Mennatullah],
Krüger, V.[Volker],
Comparative Evaluation of 3D Pose Estimation of Industrial Objects in
RGB Pointclouds,
CVS15(329-342).
Springer DOI
1507
BibRef
Nguyen, D.D.[Duc Dung],
Ko, J.P.[Jae Pil],
Jeon, J.W.[Jae Wook],
Determination of 3D object pose in point cloud with CAD model,
FCV15(1-6)
IEEE DOI
1506
feature extraction
BibRef
Shimizu, S.,
Koyasu, H.,
Kobayashi, Y.,
Kuno, Y.,
Object pose estimation using category information from a single image,
FCV15(1-4)
IEEE DOI
1506
computer vision
BibRef
Weber, S.[Simon],
Dages, T.[Thomas],
Gao, M.L.[Mao-Lin],
Cremers, D.[Daniel],
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis,
CVPR24(3131-3140)
IEEE DOI
2410
Heating systems, Manifolds, Geometry, Deep learning, Shape, Reviews,
Shape analysis, Riemannian manifolds, Finsler manifolds, Geometric deep learning
BibRef
Andreux, M.[Mathieu],
Rodolŕ, E.[Emanuele],
Aubry, M.[Mathieu],
Cremers, D.[Daniel],
Anisotropic Laplace-Beltrami Operators for Shape Analysis,
NORDIA14(299-312).
Springer DOI
1504
BibRef
Guzman-Rivera, A.[Abner],
Kohli, P.[Pushmeet],
Glocker, B.[Ben],
Shotton, J.[Jamie],
Sharp, T.[Toby],
Fitzgibbon, A.W.[Andrew W.],
Izadi, S.[Shahram],
Multi-output Learning for Camera Relocalization,
CVPR14(1114-1121)
IEEE DOI
1409
Multi-output learning; camera relocalization; diverse predictions
The pose of a camera relative to a known 3D scene with RGB-D image.
BibRef
Shotton, J.D.J.[Jamie D.J.],
Glocker, B.[Ben],
Zach, C.[Christopher],
Izadi, S.[Shahram],
Criminisi, A.[Antonio],
Fitzgibbon, A.W.[Andrew W.],
Scene Coordinate Regression Forests for Camera Relocalization in
RGB-D Images,
CVPR13(2930-2937)
IEEE DOI
1309
Infer pose relative to known 3D scene.
See also TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context.
BibRef
Barnea, E.[Ehud],
Ben-Shahar, O.[Ohad],
Contextual Object Detection with a Few Relevant Neighbors,
ACCV18(II:480-495).
Springer DOI
1906
BibRef
And:
Depth Based Object Detection from Partial Pose Estimation of Symmetric
Objects,
ECCV14(V: 377-390).
Springer DOI
1408
Partial pose from depth, match.
BibRef
Breslav, M.[Mikhail],
Hedrick, T.L.,
Sclaroff, S.[Stan],
Betke, M.[Margrit],
Discovering useful parts for pose estimation in sparsely annotated
datasets,
WACV16(1-9)
IEEE DOI
1606
Animals
BibRef
Breslav, M.[Mikhail],
Fuller, N.[Nathan],
Sclaroff, S.[Stan],
Betke, M.[Margrit],
3D pose estimation of bats in the wild,
WACV14(91-98)
IEEE DOI
1406
Cameras
BibRef
Kurmankhojayev, D.[Daniyar],
Hasler, N.[Nils],
Theobalt, C.[Christian],
Monocular Pose Capture with a Depth Camera Using a Sums-of-Gaussians
Body Model,
GCPR13(415-424).
Springer DOI
1311
BibRef
Thachasongtham, D.[Dissaphong],
Yoshida, T.[Takumi],
de Sorbier, F.[François],
Saito, H.[Hideo],
3D Object Pose Estimation Using Viewpoint Generative Learning,
SCIA13(512-521).
Springer DOI
1311
BibRef
El-Gaaly, T.[Tarek],
Torki, M.[Marwan],
RGBD object pose recognition using local-global multi-kernel regression,
ICPR12(2468-2471).
WWW Link.
1302
BibRef
Produit, T.[Timothee],
Tuia, D.[Devis],
Golay, F.[Francois],
Strecha, C.[Christoph],
Pose estimation of landscape images using DEM and orthophotos,
CVRS12(209-214).
IEEE DOI
1302
BibRef
Raytchev, B.[Bisser],
Terakado, K.[Kazuya],
Tamaki, T.[Toru],
Kaneda, K.[Kazufumi],
Pose estimation by local procrustes regression,
ICIP11(3585-3588).
IEEE DOI
1201
BibRef
Axenopoulos, A.[Apostolos],
Litos, G.[Georgios],
Daras, P.[Petros],
3D model retrieval using accurate pose estimation and view-based
similarity,
ICMR11(41).
DOI Link
1301
3D model
alignment method, combining two
criteria, the plane reflection symmetry and rectilinearity.
BibRef
Zhang, Q.[Qian],
Jia, J.Y.[Jin-Yuan],
A GPU Based High-Efficient And Accurate Optimal Pose Alignment
Approach Of 3d Objects,
3DOR11(97-100)
DOI Link
1301
BibRef
Fenzi, M.[Michele],
Leal-Taixe, L.[Laura],
Ostermann, J.[Jorn],
Tuytelaars, T.,
Continuous Pose Estimation with a Spatial Ensemble of Fisher
Regressors,
ICCV15(1035-1043)
IEEE DOI
1602
Design automation
BibRef
Fenzi, M.[Michele],
Leal-Taixe, L.[Laura],
Schindler, K.[Konrad],
Ostermann, J.[Jorn],
Pose Estimation of Object Categories in Videos Using Linear
Programming,
WACV15(821-828)
IEEE DOI
1503
Estimation
BibRef
Fenzi, M.[Michele],
Ostermann, J.[Jorn],
Embedding Geometry in Generative Models for Pose Estimation of Object
Categories,
BMVC14(xx-yy).
HTML Version.
1410
BibRef
Fenzi, M.[Michele],
Leal-Taixe, L.[Laura],
Rosenhahn, B.[Bodo],
Ostermann, J.[Jorn],
Class Generative Models Based on Feature Regression for Pose
Estimation of Object Categories,
CVPR13(755-762)
IEEE DOI
1309
Continuous pose estimation
BibRef
Soltow, E.[Erik],
Rosenhahn, B.[Bodo],
Automatic Pose Estimation Using Contour Information from X-Ray Images,
MCBMIIA15(246-257).
Springer DOI
1603
BibRef
Fenzi, M.[Michele],
Dragon, R.[Ralf],
Leal-Taixé, L.[Laura],
Rosenhahn, B.[Bodo],
Ostermann, J.[Jörn],
3d Object Recognition and Pose Estimation for Multiple Objects Using
Multi-Prioritized Ransac and Model Updating,
DAGM12(123-133).
Springer DOI
1209
BibRef
Persad, R.A.,
Armenakis, C.,
Sohn, G.,
Integration of Video Images and CAD Wireframes for 3d Object
Localization,
AnnalsPRS(I-3), No. 2012, pp. 353-358.
DOI Link
1209
BibRef
Ali, H.[Haider],
Figueroa, N.[Nadia],
Segmentation and Pose Estimation of Planar Metallic Objects,
CRV12(376-382).
IEEE DOI
1207
Segmentation by euclidean clustering, pose estimation by ICP.
Planar surfaces in laser scanner data.
BibRef
Aldoma, A.,
Vincze, M.,
Pose Alignment for 3D Models and Single View Stereo Point Clouds Based
on Stable Planes,
3DIMPVT11(374-380).
IEEE DOI
1109
BibRef
Bey, A.[Aurélien],
Chaine, R.[Raphaëlle],
Marc, R.[Raphaël],
Thibault, G.[Guillaume],
Akkouche, S.[Samir],
Reconstruction of Consistent 3D CAD Models from Point Cloud Data Using
A Priori CAD Models,
Laser11(xx-yy).
DOI Link
1109
Fitting the point cloud with the 3D model.
BibRef
Jia, H.J.[Hong-Jun],
Wu, G.R.[Guo-Rong],
Wang, Q.[Qian],
Shen, D.G.[Ding-Gang],
ABSORB: Atlas building by Self-Organized Registration and Bundling,
CVPR10(2785-2790).
IEEE DOI
1006
Register the model by deforming to each subject.
BibRef
Hebel, M.,
Arens, M.,
Stilla, U.,
Utilization of 3D City Models and Airborne Laser Scanning for
Terrain-based Navigation of Helicopters and UAVs,
CMRT09(187-192).
PDF File.
0909
Use 3D models to determine location.
BibRef
Selby, B.P.,
Sakas, G.,
Walter, S.,
Groch, W.D.,
Stilla, U.,
Detection of Pose Changes for Spatial Objects from Projective Images,
PIA07(105).
PDF File.
0711
BibRef
Guđmundsson, S.Á.[Sigurjón Árni],
Larsen, R.[Rasmus],
Ersbřll, B.K.[Bjarne K.],
Robust Pose Estimation Using the SwissRanger SR-3000 Camera,
SCIA07(968-975).
Springer DOI
0706
classify and pose from low res model and 3D data.
BibRef
Rodgers, J.[Jim],
Anguelov, D.[Dragomir],
Pang, H.C.[Hoi-Cheung],
Koller, D.[Daphne],
Object Pose Detection in Range Scan Data,
CVPR06(II: 2445-2452).
IEEE DOI
0606
BibRef
Sepp, W.,
Hirzinger, G.,
Featureless 6 DoF pose refinement from stereo images,
ICPR02(IV: 17-20).
IEEE DOI
0211
BibRef
Rui, L.,
Hirzinger, G.[Gerd],
Marker-Free Automatic Matching Of Range Data,
PanoPhot05(xx-yy).
PDF File.
0502
BibRef
Amano, T.,
Hiura, S.,
Yamaguchi, A.,
Inokuchi, S.,
Eigenispace Approach for a Pose Detection with Range Images:
Robust Pose Detection Method for Pixel Lacks of Range Images,
ICPR96(I: 622-626).
IEEE DOI
9608
(Osaka Univ., J)
BibRef
Beveridge, J.R.[J. Ross], and
Schwickerath, A.N.A.[Anthony N.A.],
Object to Multisensor Coregistration with Eight Degrees of Freedom,
ARPA94(I:481-490).
PS File.
BibRef
9400
Schwickerath, A.N.A.[Anthony N.A.],
Beveridge, J.R.[J. Ross],
Coregistration of Range and Optical Images Using Coplanarity and
Orientation Constraints,
CVPR96(899-906).
IEEE DOI
PS File.
BibRef
9600
Schwickerath, A.N.A.,
Beveridge, J.R.,
Coregistering 3D Models, Range, and Optical Imagery Using
Least-Median Squares Fitting,
ARPA96(719-722).
PS File.
BibRef
9600
Pipitone, F.,
Adams, W.,
Rapid recognition of freeform objects in noisy range images using
tripod operators,
CVPR93(715-716).
IEEE DOI
0403
BibRef
Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
6D Object Pose Estimation .