Sahin, C.[Caner],
Kouskouridas, R.[Rigas],
Kim, T.K.[Tae-Kyun],
A learning-based variable size part extraction architecture for 6D
object pose recovery in depth images,
IVC(63), No. 1, 2017, pp. 38-50.
Elsevier DOI
1706
Object registration
BibRef
Doumanoglou, A.[Andreas],
Kouskouridas, R.[Rigas],
Malassiotis, S.[Sotiris],
Kim, T.K.[Tae-Kyun],
Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd,
CVPR16(3583-3592)
IEEE DOI
1612
BibRef
Zhang, H.[Haoruo],
Cao, Q.X.[Qi-Xin],
Holistic and local patch framework for 6D object pose estimation in
RGB-D images,
CVIU(180), 2019, pp. 59-73.
Elsevier DOI
1903
6D object pose estimation, RGB-D images, Holistic patch,
Local patch, Convolutional neural network, Particle swarm optimization
BibRef
Kaskman, R.,
Zakharov, S.,
Shugurov, I.,
Ilic, S.,
HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objects,
R6D19(2767-2776)
IEEE DOI
2004
image colour analysis, learning (artificial intelligence),
object detection, pose estimation, solid modelling, deep learning,
6D Pose Estimation
BibRef
Zakharov, S.,
Shugurov, I.,
Ilic, S.,
DPOD: 6D Pose Object Detector and Refiner,
ICCV19(1941-1950)
IEEE DOI
2004
image colour analysis, learning (artificial intelligence),
object detection, pose estimation, solid modelling, input image,
Training data
BibRef
Zhou, G.L.[Guang-Liang],
Yan, Y.[Yi],
Wang, D.[Deming],
Chen, Q.J.[Qi-Jun],
A Novel Depth and Color Feature Fusion Framework for 6D Object Pose
Estimation,
MultMed(23), 2021, pp. 1630-1639.
IEEE DOI
2106
Pose estimation,
Image color analysis, Feature extraction, Color,
region-level feature
BibRef
Shugurov, I.[Ivan],
Zakharov, S.[Sergey],
Ilic, S.[Slobodan],
DPODv2: Dense Correspondence-Based 6 DoF Pose Estimation,
PAMI(44), No. 11, November 2022, pp. 7417-7435.
IEEE DOI
2210
Pose estimation, Detectors, Deep learning, Training data,
Solid modeling, 6 DoF pose estimation, dense correspondences, synthetic data
BibRef
Huang, J.W.[Jun-Wen],
Yu, H.[Hao],
Yu, K.T.[Kuan-Ting],
Navab, N.[Nassir],
Ilic, S.[Slobodan],
Busam, B.[Benjamin],
MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D
Images,
CVPR24(10095-10105)
IEEE DOI
2410
Geometry, Training, Point cloud compression, Solid modeling, Fuses,
Scalability, 6D pose estimation, descriptor learning,
unseen object pose estimation
BibRef
Pitteri, G.,
Ramamonjisoa, M.,
Ilic, S.[Slobodan],
Lepetit, V.[Vincent],
On Object Symmetries and 6D Pose Estimation from Images,
3DV19(614-622)
IEEE DOI
1911
Pose estimation, Training, Measurement,
Machine learning algorithms,
Deep Learning
BibRef
Wu, C.R.[Chen-Rui],
Chen, L.[Long],
Wang, S.L.[Sheng-Long],
Yang, H.[Han],
Jiang, J.J.[Jun-Jie],
Geometric-aware dense matching network for 6D pose estimation of
objects from RGB-D images,
PR(137), 2023, pp. 109293.
Elsevier DOI
2302
6D pose estimation, Metric learning, Triplet loss,
Dense correspondences, Geometric constraint
BibRef
Zhang, J.H.[Jia-Hui],
Shi, J.L.[Jin-Long],
Zou, D.P.[Dan-Ping],
Shu, X.[Xin],
Bai, S.[Suqin],
Lu, J.[Jiawen],
Zhu, H.[Haowei],
Ni, J.[Jun],
Sun, Y.H.[Yun-Han],
EPM-Net: Efficient Feature Extraction, Point-Pair Feature Matching
for Robust 6-D Pose Estimation,
MultMed(26), 2024, pp. 5120-5130.
IEEE DOI
2404
Feature extraction, Pose estimation, Solid modeling,
Point cloud compression, Cameras, Data mining, Robustness,
RGB-D images
BibRef
Cao, T.[Tuo],
Zhang, W.X.[Wen-Xiao],
Fu, Y.P.[Yan-Ping],
Zheng, S.J.[Sheng-Jie],
Luo, F.[Fei],
Xiao, C.X.[Chun-Xia],
DGECN++: A Depth-Guided Edge Convolutional Network for End-to-End 6D
Pose Estimation via Attention Mechanism,
CirSysVideo(34), No. 6, June 2024, pp. 4214-4228.
IEEE DOI
2406
BibRef
Earlier: A1, A5, A3, A2, A4, A6:
DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D
Pose Estimation,
CVPR22(3773-3782)
IEEE DOI
2210
Pose estimation, Feature extraction,
Convolutional neural networks, Prediction algorithms, attention mechanism.
Uncertainty, Network topology, Pipelines,
Robustness, 3D from single images
BibRef
Zhou, J.[Jun],
Chen, K.[Kai],
Wei, M.Q.[Ming-Qiang],
Zhang, X.P.[Xiao-Ping],
Dou, Q.[Qi],
Qin, J.[Jing],
Canonical Shape Reconstruction With SE(3) Equivariance Learning for
Weakly-Supervised Object Pose Estimation,
CirSysVideo(35), No. 7, July 2025, pp. 6895-6909.
IEEE DOI
2507
6D object pose estimation from a single RGB-D image.
Shape, Training, Point cloud compression, Pose estimation,
Solid modeling, Image reconstruction, Feature extraction, Geometry,
SE(3) equivariance
BibRef
Petitjean, T.[Théo],
Wu, Z.W.[Zong-Wei],
Laligant, O.[Olivier],
Demonceaux, C.[Cédric],
QaQ: Robust 6D Pose Estimation via Quality-Assessed RGB-D Fusion,
MVA23(1-7)
DOI Link
2403
Fuses, Machine vision, Aggregates, Pose estimation, Color, Robustness,
Noise measurement
BibRef
Fan, Z.X.[Zhao-Xin],
Song, Z.B.[Zhen-Bo],
Xu, J.[Jian],
Wang, Z.C.[Zhi-Cheng],
Wu, K.J.[Ke-Jian],
Liu, H.Y.[Hong-Yan],
He, J.[Jun],
Object Level Depth Reconstruction for Category Level 6D Object Pose
Estimation from Monocular RGB Image,
ECCV22(II:220-236).
Springer DOI
2211
BibRef
Wu, Y.Z.[Yang-Zheng],
Zand, M.[Mohsen],
Etemad, A.[Ali],
Greenspan, M.[Michael],
Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial
Keypoint Voting,
ECCV22(X:335-352).
Springer DOI
2211
BibRef
Lin, Y.L.[Yong-Liang],
Su, Y.Z.[Yong-Zhi],
Nathan, P.[Praveen],
Inuganti, S.[Sandeep],
Di, Y.[Yan],
Sundermeyer, M.[Martin],
Manhardt, F.[Fabian],
Stricker, D.[Didier],
Rambach, J.[Jason],
Zhang, Y.[Yu],
HiPose: Hierarchical Binary Surface Encoding and Correspondence
Pruning for RGB-D 6DoF Object Pose Estimation,
CVPR24(10148-10158)
IEEE DOI
2410
Accuracy, Pose estimation, Benchmark testing,
Rendering (computer graphics), Encoding, Real-time systems, RGB-D
BibRef
Su, Y.Z.[Yong-Zhi],
Saleh, M.[Mahdi],
Fetzer, T.[Torben],
Rambach, J.[Jason],
Navab, N.[Nassir],
Busam, B.[Benjamin],
Stricker, D.[Didier],
Tombari, F.[Federico],
ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose
Estimation,
CVPR22(6728-6738)
IEEE DOI
2210
Training, Measurement, Codes, Pose estimation, Robot vision systems,
Object segmentation, Pose estimation and tracking, Robot vision
BibRef
Jiang, X.[Xiaoke],
Li, D.H.[Dong-Hai],
Chen, H.[Hao],
Zheng, Y.[Ye],
Zhao, R.[Rui],
Wu, L.W.[Li-Wei],
Uni6D: A Unified CNN Framework without Projection Breakdown for 6D
Pose Estimation,
CVPR22(11164-11174)
IEEE DOI
2210
Training, Solid modeling, Head, Electric breakdown, Pose estimation,
Pipelines, RGBD sensors and analytics, Robot vision
BibRef
Cai, D.D.[Ding-Ding],
Heikkiä, J.[Janne],
Rahtu, E.[Esa],
OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose
Estimation,
CVPR22(6793-6803)
IEEE DOI
2210
Training, Pose estimation, Training data, Optical imaging, Cameras,
Encoding, Pose estimation and tracking, Recognition: detection,
RGBD sensors and analytics
BibRef
Feng, H.T.[Hang-Tao],
Zhang, L.[Lu],
Yang, X.[Xu],
Liu, Z.Y.[Zhi-Yong],
MixedFusion: 6D Object Pose Estimation from Decoupled RGB-Depth
Features,
ICPR21(685-691)
IEEE DOI
2105
Measurement, Image color analysis,
Fuses, Pose estimation, Color
BibRef
Cheng, Y.[Yi],
Zhu, H.Y.[Hong-Yuan],
Sun, Y.[Ying],
Acar, C.[Cihan],
Jing, W.[Wei],
Wu, Y.[Yan],
Li, L.Y.[Li-Yuan],
Tan, C.[Cheston],
Lim, J.H.[Joo-Hwee],
6D Pose Estimation with Correlation Fusion,
ICPR21(2988-2994)
IEEE DOI
2105
Correlation, Pose estimation, Lighting, Grasping, Benchmark testing,
Task analysis, object pose estimation, RGB-D, correlation fusion
BibRef
Song, J.R.[Jing-Rui],
Hao, S.[Shuling],
Xu, K.[Kefeng],
Uncooperative Satellite 6D Pose Estimation with Relative Depth
Information,
ISVC21(II:166-177).
Springer DOI
2112
BibRef
Hu, Y.L.[Yin-Lin],
Speierer, S.[Sébastien],
Jakob, W.[Wenzel],
Fua, P.[Pascal],
Salzmann, M.[Mathieu],
Wide-Depth-Range 6D Object Pose Estimation in Space,
CVPR21(15865-15874)
IEEE DOI
2111
Training, Solid modeling, Satellites,
Pose estimation, Scattering, Benchmark testing
BibRef
Cunico, F.[Federico],
Carletti, M.[Marco],
Cristani, M.[Marco],
Masci, F.[Fabio],
Conigliaro, D.[Davide],
6D Pose Estimation for Industrial Applications,
NTIAP19(374-384).
Springer DOI
1909
From both RGB and depth information.
BibRef
Sahin, C.[Caner],
Kim, T.K.[Tae-Kyun],
Category-Level 6D Object Pose Recovery in Depth Images,
4DPose18(I:665-681).
Springer DOI
1905
BibRef
Sock, J.,
Kasaei, S.H.,
Lopes, L.S.,
Kim, T.K.,
Multi-view 6D Object Pose Estimation and Camera Motion Planning Using
RGBD Images,
6DPose17(2228-2235)
IEEE DOI
1802
Cameras, Entropy, Object detection, Object recognition, Planning,
Pose estimation
BibRef
Balntas, V.,
Doumanoglou, A.,
Sahin, C.,
Sock, J.,
Kouskouridas, R.,
Kim, T.K.,
Pose Guided RGBD Feature Learning for 3D Object Pose Estimation,
ICCV17(3876-3884)
IEEE DOI
1802
correlation methods, feature extraction,
learning (artificial intelligence), pose estimation,
Training
BibRef
Basevi, H.[Hector],
Leonardis, A.[Aleš],
Towards Categorization and Pose Estimation of Sets of Occluded Objects
in Cluttered Scenes from Depth Data and Generic Object Models Using
Joint Parsing,
6DPose16(III: 665-681).
Springer DOI
1611
BibRef
Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Laplace-Beltrami Operator, Beltrami Flow .