mlsanityData to 7 Oct 2026

ES6D: A Computation Efficient and Symmetry-Aware 6D Pose Regression Framework

arXiv 2204.01080 ↗First posted 3 Apr 2022cs.CVcited by 19

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Abstract (arXiv)

In this paper, a computation efficient regression framework is presented for estimating the 6D pose of rigid objects from a single RGB-D image, which is applicable to handling symmetric objects. This framework is designed in a simple architecture that efficiently extracts point-wise features from RGB-D data using a fully convolutional network, called XYZNet, and directly regresses the 6D pose without any post refinement. In the case of symmetric object, one object has multiple ground-truth poses, and this one-to-many relationship may lead to estimation ambiguity. In order to solve this ambiguity problem, we design a symmetry-invariant pose distance metric, called average (maximum) grouped primitives distance or A(M)GPD. The proposed A(M)GPD loss can make the regression network converge to the correct state, i.e., all minima in the A(M)GPD loss surface are mapped to the correct poses. Extensive experiments on YCB-Video and T-LESS datasets demonstrate the proposed framework's substantially superior performance in top accuracy and low computational cost.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 30 of its 41 references that are in the map. First posted on arXiv 3 Apr 2022.

Builds on

30 of 41 references.

References · 30

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  3. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  4. 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,186
  5. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 768
  6. 2016Multi-View 3D Object Detection Network for Autonomous Drivingcited by 721
  7. 2019Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimationcited by 490
  8. 2018PVNet: Pixel-wise Voting Network for 6DoF Pose Estimationcited by 385
  9. 2019DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusioncited by 352
  10. 2019Point-Voxel CNN for Efficient 3D Deep Learningcited by 343
  11. 2020CosyPose: Consistent multi-view multi-object 6D pose estimationcited by 287
  12. 2018Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objectscited by 237
18 more
  1. 2017BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depthcited by 225
  2. 2019Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimationcited by 218
  3. 2017T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objectscited by 210
  4. 2019PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimationcited by 204
  5. 2020BOP Challenge 2020 on 6D Object Localizationcited by 192
  6. 2019DPOD: 6D Pose Object Detector and Refinercited by 189
  7. 2018PPFNet: Global Context Aware Local Features for Robust 3D Point Matchingcited by 180
  8. 2020EPOS: Estimating 6D Pose of Objects with Symmetriescited by 147
  9. 2021FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimationcited by 144
  10. 2017Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activationscited by 104
  11. 2018A Unified Framework for Multi-View Multi-Class Object Pose Estimationcited by 49
  12. 2019On Object Symmetries and 6D Pose Estimation from Imagescited by 33
  13. 20206D Object Pose Regression via Supervised Learning on Point Cloudscited by 33
  14. 2016Defining the Pose of any 3D Rigid Object and an Associated Distancecited by 17
  15. 2021StablePose: Learning 6D Object Poses from Geometrically Stable Patchescited by 17
  16. 2020REDE: End-to-end Object 6D Pose Robust Estimation Using Differentiable Outliers Eliminationcited by 7
  17. 2019W-PoseNet: Dense Correspondence Regularized Pixel Pair Pose Regressioncited by 6
  18. 2020PAM:Point-wise Attention Module for 6D Object Pose Estimationcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 8; 2024: 4; 2025: 2; 2026: 3.

19 papers.

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  1. 2023HS-Pose: Hybrid Scope Feature Extraction for Category-level Object Pose Estimationcited by 47
  2. 2024Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose Estimationcited by 41
  3. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 39
  4. 2024RDPN6D: Residual-based Dense Point-wise Network for 6Dof Object Pose Estimation Based on RGB-D Imagescited by 5
  5. 2025GIVEPose: Gradual Intra-class Variation Elimination for RGB-based Category-Level Object Pose Estimationcited by 5
  6. 2025CAP-Net: A Unified Network for 6D Pose and Size Estimation of Categorical Articulated Parts from a Single RGB-D Imagecited by 5
  7. 2022Uni6Dv2: Noise Elimination for 6D Pose Estimationcited by 4
  8. 2023SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimationcited by 4
  9. 2023Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking Applicationscited by 3
  10. 2022Geo6D: Geometric Constraints Learning for 6D Pose Estimationcited by 2
  11. 2023S2P3: Self-Supervised Polarimetric Pose Predictioncited by 2
  12. 2023Active Semantic Localization with Graph Neural Embeddingcited by 1
7 more
  1. 2023Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Datasetcited by 1
  2. 2024Resolving Symmetry Ambiguity in Correspondence-based Methods for Instance-level Object Pose Estimationcited by 1
  3. 2026Towards Symmetry-sensitive Pose Estimation: A Rotation Representation for Symmetric Object Classescited by 1
  4. 2023A Multi-modal Approach to Single-modal Visual Place Classificationcited by 0
  5. 2023Polarimetric Information for Multi-Modal 6D Pose Estimation of Photometrically Challenging Objects with Limited Datacited by 0
  6. 2026Rotational Symmetry based Object Pose Estimation from Point Clouds in the Absence of Known 3D Modelscited by 0
  7. 2026A Geometry-Driven, Framework-Agnostic Optimization for Object Pose Estimationcited by 0