mlsanityData to 13 Oct 2026

BOP-Distrib: Revisiting 6D Pose Estimation Benchmarks for Better Evaluation under Visual Ambiguities

arXiv 2408.17297 ↗First posted 30 Aug 2024cs.CVcited by 3

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Abstract (arXiv)

6D pose estimation aims at determining the object pose that best explains the camera observation. The unique solution for non-ambiguous objects can turn into a multi-modal pose distribution for symmetrical objects or when occlusions of symmetry-breaking elements happen, depending on the viewpoint. Currently, 6D pose estimation methods are benchmarked on datasets that consider, for their ground truth annotations, visual ambiguities as only related to global object symmetries, whereas they should be defined per-image to account for the camera viewpoint. We thus first propose an automatic method to re-annotate those datasets with a 6D pose distribution specific to each image, taking into account the object surface visibility in the image to correctly determine the visual ambiguities. Second, given this improved ground truth, we re-evaluate the state-of-the-art single pose methods and show that this greatly modifies the ranking of these methods. Third, as some recent works focus on estimating the complete set of solutions, we derive a precision/recall formulation to evaluate them against our image-wise distribution ground truth, making it the first benchmark for pose distribution methods on real images.

Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). Builds on 40 of its 58 references that are in the map. First posted on arXiv 30 Aug 2024.

Builds on

40 of 58 references.

References · 40

  1. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 770
  2. 2023FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objectscited by 415
  3. 2020CosyPose: Consistent multi-view multi-object 6D pose estimationcited by 287
  4. 2018BOP: Benchmark for 6D Object Pose Estimationcited by 254
  5. 2019Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimationcited by 218
  6. 2017T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objectscited by 210
  7. 2022MegaPose: 6D Pose Estimation of Novel Objects via Render & Comparecited by 200
  8. 2020BOP Challenge 2020 on 6D Object Localizationcited by 192
  9. 2021GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimatorcited by 148
  10. 2020EPOS: Estimating 6D Pose of Objects with Symmetriescited by 147
  11. 2023SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimationcited by 117
  12. 2022ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimationcited by 115
28 more
  1. 2023GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondencecited by 113
  2. 2019HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objectscited by 110
  3. 2023FoundPose: Unseen Object Pose Estimation with Foundation Featurescited by 109
  4. 2021SurfEmb: Dense and Continuous Correspondence Distributions for Object Pose Estimation with Learnt Surface Embeddingscited by 95
  5. 2023CNOS: A Strong Baseline for CAD-based Novel Object Segmentationcited by 86
  6. 20226-DoF Pose Estimation of Household Objects for Robotic Manipulation: An Accessible Dataset and Benchmarkcited by 85
  7. 2015Recovering 6D Object Pose and Predicting Next-Best-View in the Crowdcited by 79
  8. 2023BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objectscited by 70
  9. 2018Explaining the Ambiguity of Object Detection and 6D Pose From Visual Datacited by 68
  10. 2021Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifoldcited by 65
  11. 2024BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objectscited by 60
  12. 2022PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objectscited by 45
  13. 2020Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimationcited by 43
  14. 2024GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objectscited by 32
  15. 20206D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inferencecited by 23
  16. 2023ZeroPose: CAD-Prompted Zero-shot Object 6D Pose Estimation in Cluttered Scenescited by 20
  17. 2016Defining the Pose of any 3D Rigid Object and an Associated Distancecited by 18
  18. 2020Learning Orientation Distributions for Object Pose Estimationcited by 18
  19. 2023Image to Sphere: Learning Equivariant Features for Efficient Pose Predictioncited by 18
  20. 2022SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose Estimationcited by 17
  21. 2023Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)cited by 17
  22. 2023HiPose: Hierarchical Binary Surface Encoding and Correspondence Pruning for RGB-D 6DoF Object Pose Estimationcited by 17
  23. 2022FisherMatch: Semi-Supervised Rotation Regression via Entropy-based Filteringcited by 16
  24. 2023SpyroPose: SE(3) Pyramids for Object Pose Distribution Estimationcited by 14
  25. 2018Symmetry Aware Evaluation of 3D Object Detection and Pose Estimation in Scenes of Many Parts in Bulkcited by 12
  26. 2024MRC-Net: 6-DoF Pose Estimation with MultiScale Residual Correlationcited by 11
  27. 2022Ki-Pode: Keypoint-based Implicit Pose Distribution Estimation of Rigid Objectscited by 7
  28. 2022Learning Implicit Probability Distribution Functions for Symmetric Orientation Estimation from RGB Images Without Pose Labelscited by 2

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025Corr2Distrib: Making Ambiguous Correspondences an Ally to Predict Reliable 6D Pose Distributionscited by 3
  2. 2025IMD: A 6-DoF Pose Estimation Benchmark for Industrial Metallic Objectscited by 0
  3. 2026MHE-Former: Multi-Hypothesis Transformers via Entropy Maximization for 3D Mesh Recoverycited by 0