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HybridPose: 6D Object Pose Estimation under Hybrid Representations

arXiv 2001.01869 ↗First posted 7 Jan 2020cs.CVcited by 107

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Abstract (arXiv)

We introduce HybridPose, a novel 6D object pose estimation approach. HybridPose utilizes a hybrid intermediate representation to express different geometric information in the input image, including keypoints, edge vectors, and symmetry correspondences. Compared to a unitary representation, our hybrid representation allows pose regression to exploit more and diverse features when one type of predicted representation is inaccurate (e.g., because of occlusion). Different intermediate representations used by HybridPose can all be predicted by the same simple neural network, and outliers in predicted intermediate representations are filtered by a robust regression module. Compared to state-of-the-art pose estimation approaches, HybridPose is comparable in running time and accuracy. For example, on Occlusion Linemod dataset, our method achieves a prediction speed of 30 fps with a mean ADD(-S) accuracy of 47.5%, representing a state-of-the-art performance. The implementation of HybridPose is available at https://github.com/chensong1995/HybridPose.

Key facts. Cited by 107 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jan 2020.

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Citing papers per year: 2021: 28; 2022: 38; 2023: 16; 2024: 15; 2025: 5; 2026: 5.

107 papers.

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  1. 2022MegaPose: 6D Pose Estimation of Novel Objects via Render & Comparecited by 198
  2. 2021GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimatorcited by 148
  3. 2021FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimationcited by 144
  4. 2022Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Imagescited by 120
  5. 2022ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimationcited by 115
  6. 2023FoundPose: Unseen Object Pose Estimation with Foundation Featurescited by 109
  7. 2022RelPose: Predicting Probabilistic Relative Rotation for Single Objects in the Wildcited by 102
  8. 2022GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Votingcited by 94
  9. 2021SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimationcited by 88
  10. 2022OSOP: A Multi-Stage One Shot Object Pose Estimation Frameworkcited by 81
  11. 2023EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimationcited by 79
  12. 2021Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networkscited by 69
38 more
  1. 2021RePOSE: Fast 6D Object Pose Refinement via Deep Texture Renderingcited by 63
  2. 2022NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimationcited by 57
  3. 2021SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimationcited by 53
  4. 2021Wide-Depth-Range 6D Object Pose Estimation in Spacecited by 45
  5. 2022RBP-Pose: Residual Bounding Box Projection for Category-Level Pose Estimationcited by 43
  6. 2021Single-Stage Keypoint-Based Category-Level Object Pose Estimation from an RGB Imagecited by 42
  7. 2021NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimationcited by 41
  8. 2022SSP-Pose: Symmetry-Aware Shape Prior Deformation for Direct Category-Level Object Pose Estimationcited by 41
  9. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 39
  10. 2022RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose Optimizationcited by 38
  11. 2021HPNet: Deep Primitive Segmentation Using Hybrid Representationscited by 35
  12. 2022Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimationcited by 34
  13. 2021Single-view robot pose and joint angle estimation via render & comparecited by 33
  14. 2022Perspective Flow Aggregation for Data-Limited 6D Object Pose Estimationcited by 32
  15. 2022DPODv2: Dense Correspondence-Based 6 DoF Pose Estimationcited by 32
  16. 2021Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overviewcited by 31
  17. 2021VS-Net: Voting with Segmentation for Visual Localizationcited by 29
  18. 2021Scene Synthesis via Uncertainty-Driven Attribute Synchronizationcited by 29
  19. 2022Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Imagecited by 29
  20. 2022CATRE: Iterative Point Clouds Alignment for Category-level Object Pose Refinementcited by 28
  21. 20236D-Diff: A Keypoint Diffusion Framework for 6D Object Pose Estimationcited by 24
  22. 2022Uni6D: A Unified CNN Framework without Projection Breakdown for 6D Pose Estimationcited by 22
  23. 2023Challenges for Monocular 6D Object Pose Estimation in Roboticscited by 21
  24. 20216D-ViT: Category-Level 6D Object Pose Estimation via Transformer-based Instance Representation Learningcited by 20
  25. 2021ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimationcited by 20
  26. 2023Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Imagescited by 18
  27. 2021StablePose: Learning 6D Object Poses from Geometrically Stable Patchescited by 17
  28. 2021PR-GCN: A Deep Graph Convolutional Network with Point Refinement for 6D Pose Estimationcited by 17
  29. 2022Focal Length and Object Pose Estimation via Render and Comparecited by 17
  30. 2022SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose Estimationcited by 17
  31. 2021Polarimetric Pose Predictioncited by 16
  32. 2023Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimationcited by 16
  33. 2023CheckerPose: Progressive Dense Keypoint Localization for Object Pose Estimation with Graph Neural Networkcited by 15
  34. 2021DSC-PoseNet: Learning 6DoF Object Pose Estimation via Dual-scale Consistencycited by 14
  35. 2024LaPose: Laplacian Mixture Shape Modeling for RGB-Based Category-Level Object Pose Estimationcited by 13
  36. 2022DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimationcited by 12
  37. 2022HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillationcited by 11
  38. 2023Diff-DOPE: Differentiable Deep Object Pose Estimationcited by 11

50 most cited of 107 All 107 (JSON)