mlsanityData to 14 Oct 2026

Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd

arXiv 1512.07506 ↗First posted 23 Dec 2015cs.CVcited by 79

Not on the map. Why?

Abstract (arXiv)

Object detection and 6D pose estimation in the crowd (scenes with multiple object instances, severe foreground occlusions and background distractors), has become an important problem in many rapidly evolving technological areas such as robotics and augmented reality. Single shot-based 6D pose estimators with manually designed features are still unable to tackle the above challenges, motivating the research towards unsupervised feature learning and next-best-view estimation. In this work, we present a complete framework for both single shot-based 6D object pose estimation and next-best-view prediction based on Hough Forests, the state of the art object pose estimator that performs classification and regression jointly. Rather than using manually designed features we a) propose an unsupervised feature learnt from depth-invariant patches using a Sparse Autoencoder and b) offer an extensive evaluation of various state of the art features. Furthermore, taking advantage of the clustering performed in the leaf nodes of Hough Forests, we learn to estimate the reduction of uncertainty in other views, formulating the problem of selecting the next-best-view. To further improve pose estimation, we propose an improved joint registration and hypotheses verification module as a final refinement step to reject false detections. We provide two additional challenging datasets inspired from realistic scenarios to extensively evaluate the state of the art and our framework. One is related to domestic environments and the other depicts a bin-picking scenario mostly found in industrial settings. We show that our framework significantly outperforms state of the art both on public and on our datasets.

Key facts. Cited by 79 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Dec 2015.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 6; 2022: 13; 2023: 12; 2024: 12; 2025: 25; 2026: 11.

79 papers.

Sort:

By area:

  1. 2022MegaPose: 6D Pose Estimation of Novel Objects via Render & Comparecited by 201
  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. 2023GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondencecited by 114
  5. 2023FoundPose: Unseen Object Pose Estimation with Foundation Featurescited by 109
  6. 2021SurfEmb: Dense and Continuous Correspondence Distributions for Object Pose Estimation with Learnt Surface Embeddingscited by 95
  7. 2023CNOS: A Strong Baseline for CAD-based Novel Object Segmentationcited by 87
  8. 20226-DoF Pose Estimation of Household Objects for Robotic Manipulation: An Accessible Dataset and Benchmarkcited by 86
  9. 2023BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objectscited by 70
  10. 2024BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objectscited by 60
  11. 2023FreeZe: Training-free zero-shot 6D pose estimation with geometric and vision foundation modelscited by 57
  12. 2022HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarioscited by 53
38 more
  1. 2022PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objectscited by 45
  2. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 40
  3. 2024GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objectscited by 33
  4. 2022DPODv2: Dense Correspondence-Based 6 DoF Pose Estimationcited by 32
  5. 2024MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D Imagescited by 28
  6. 2022Uni6D: A Unified CNN Framework without Projection Breakdown for 6D Pose Estimationcited by 22
  7. 2022Interactron: Embodied Adaptive Object Detectioncited by 21
  8. 2023Challenges for Monocular 6D Object Pose Estimation in Roboticscited by 21
  9. 2025BOP Challenge 2024 on Model-Based and Model-Free 6D Object Pose Estimationcited by 19
  10. 2024Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentationcited by 17
  11. 2025Co-op: Correspondence-based Novel Object Pose Estimationcited by 14
  12. 2023Rigidity-Aware Detection for 6D Object Pose Estimationcited by 13
  13. 2025Accurate and efficient zero-shot 6D pose estimation with frozen foundation modelscited by 13
  14. 2022Spacecraft Pose Estimation Based on Unsupervised Domain Adaptation and on a 3D-Guided Loss Combinationcited by 12
  15. 2024Object Pose Estimation via the Aggregation of Diffusion Featurescited by 12
  16. 2025Scalable Unseen Objects 6-DoF Absolute Pose Estimation with Robotic Integrationcited by 11
  17. 2022COPE: End-to-end trainable Constant Runtime Object Pose Estimationcited by 10
  18. 2025GoTrack: Generic 6DoF Object Pose Refinement and Trackingcited by 10
  19. 2022Semantic keypoint-based pose estimation from single RGB framescited by 7
  20. 2025XYZ-IBD: Benchmarking Robust 6D Object Pose Estimation under Real-World Industrial Complexitycited by 7
  21. 2023Active Open-Vocabulary Recognition: Let Intelligent Moving Mitigate CLIP Limitationscited by 6
  22. 2025PicoPose: Progressive Pixel-to-Pixel Correspondence Learning for Novel Object Pose Estimationcited by 6
  23. 2022ParaPose: Parameter and Domain Randomization Optimization for Pose Estimation using Synthetic Datacited by 5
  24. 2024Structure from Duplicates: Neural Inverse Graphics from a Pile of Objectscited by 5
  25. 2021Next-best-view Regression using a 3D Convolutional Neural Networkcited by 4
  26. 2023Pseudo-keypoint RKHS Learning for Self-supervised 6DoF Pose Estimationcited by 4
  27. 2024Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patchescited by 4
  28. 2025Distilling 3D distinctive local descriptors for 6D pose estimationcited by 4
  29. 2025RayPose: Ray Bundling Diffusion for Template Views in Unseen 6D Object Pose Estimationcited by 4
  30. 2022BiCo-Net: Regress Globally, Match Locally for Robust 6D Pose Estimationcited by 3
  31. 2024Comparative Evaluation of 3D Reconstruction Methods for Object Pose Estimationcited by 3
  32. 2024BOP-Distrib: Revisiting 6D Pose Estimation Benchmarks for Better Evaluation under Visual Ambiguitiescited by 3
  33. 2024A Low-Cost, High-Speed, and Robust Bin Picking System for Factory Automation Enabled by a Non-Stop, Multi-View, and Active Vision Schemecited by 3
  34. 2025Active 6D Pose Estimation for Textureless Objects using Multi-View RGB Framescited by 3
  35. 2025HccePose(BF): Predicting Front & Back Surfaces to Construct Ultra-Dense 2D-3D Correspondences for Pose Estimationcited by 3
  36. 2025MUSE: Model-based Uncertainty-aware Similarity Estimation for zero-shot 2D Object Detection and Segmentationcited by 3
  37. 2021Active Safety Envelopes using Light Curtains with Probabilistic Guaranteescited by 2
  38. 2023Open Challenges for Monocular Single-shot 6D Object Pose Estimationcited by 2

50 most cited of 79 All 79 (JSON)