6D Object Pose Estimation Enhanced by Structural Constraint; [结构化约束增强的 6D 物体位姿估计] - Details

Author：

Wang, L. (Wang, L..) | Yang, C. (Yang, C..) | Fu, F. (Fu, F..)

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Scopus

Abstract：

Aiming　at　the　problem　that　the　6D　object　pose　estimation　method　based　on　the　voting　strategy　ignores　the　structural　information　between　keypoints,　a　6D　object　pose　estimation　method　enhanced　by　structural　constraint,　SC-Pose,　is　proposed.　This　method　defines　a　shape　descriptor　to　describe　the　structural　information　between　the　2D　keypoints　of　the　object.　By　increasing　the　keypoint　structural　loss　to　constrain　the　predicted　shape　descriptor　to　be　close　to　the　ground-truth　shape　descriptor,　the　positioning　of　the　2D　keypoints　is　more　accurate,　thereby　ultimately　enhancing　the　accuracy　of　6D　object　pose　estimation.　Results　on　the　LINEMOD,　OCC-LINEMOD　and　TruncationLINEMOD　datasets　show　that　SC-Pose　can　significantly　boost　the　accuracy　of　6D　object　pose　estimation.　©　2025　Beijing　University　of　Technology.　All　rights　reserved.

Keyword：

structural loss unit vector-field deep network grasping interaction 6D object pose estimation voting strategy

Author Community：

[ 1 ] [Wang L.]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Wang L.]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Yang C.]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 4 ] [Yang C.]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing, 100124, China
[ 5 ] [Fu F.]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 6 ] [Fu F.]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing, 100124, China

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Related Keywords：

Distance-Aware Vector-Field and Vector Screening Strategy for 6D Object Pose Estimation
2023，12th International Conference on Image and Graphics, ICIG 2023
Low-Quality Rendering-Driven 6D Object Pose Estimation from Single RGB Image
2020，International Joint Conference on Neural Networks (IJCNN) held as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)
Attention Guided 6D Object Pose Estimation with Multi-constraints Voting Network
2022，
Low-Quality Rendering-Driven 6D Object Pose Estimation from Single RGB Image
2020，2020 International Joint Conference on Neural Networks, IJCNN 2020

Source ：

Journal of Beijing University of Technology

ISSN： 0254-0037

Year： 2025

Issue： 2

Volume： 51

Page： 173-182

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ESI Highly Cited Papers on the List： 0 Unfold All

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30 Days PV： 7

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