mlsanityData to 7 Oct 2026

Going Further with Point Pair Features

arXiv 1711.04061 ↗First posted 11 Nov 2017cs.CVcited by 28

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Abstract (arXiv)

Point Pair Features is a widely used method to detect 3D objects in point clouds, however they are prone to fail in presence of sensor noise and background clutter. We introduce novel sampling and voting schemes that significantly reduces the influence of clutter and sensor noise. Our experiments show that with our improvements, PPFs become competitive against state-of-the-art methods as it outperforms them on several objects from challenging benchmarks, at a low computational cost.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Nov 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 9; 2023: 6; 2024: 6; 2025: 1; 2026: 1.

28 papers.

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  1. 2021DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistencycited by 103
  2. 2022FS6D: Few-Shot 6D Pose Estimation of Novel Objectscited by 81
  3. 2023HS-Pose: Hybrid Scope Feature Extraction for Category-level Object Pose Estimationcited by 47
  4. 2022Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimationcited by 34
  5. 2022DPODv2: Dense Correspondence-Based 6 DoF Pose Estimationcited by 32
  6. 2022CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wildcited by 28
  7. 2021ZePHyR: Zero-shot Pose Hypothesis Ratingcited by 26
  8. 2022RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registrationcited by 25
  9. 2022Neural Correspondence Field for Object Pose Estimationcited by 21
  10. 2021DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstrationcited by 20
  11. 2023Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Imagescited by 18
  12. 2023Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimationcited by 16
16 more
  1. 2024Multiway Point Cloud Mosaicking with Diffusion and Global Optimizationcited by 14
  2. 2023PoseMatcher: One-shot 6D Object Pose Estimation by Deep Feature Matchingcited by 12
  3. 2021Estimating 3D Motion and Forces of Human-Object Interactions from Internet Videoscited by 9
  4. 2022OSSID: Online Self-Supervised Instance Detection by (and for) Pose Estimationcited by 8
  5. 2023Depth-based 6DoF Object Pose Estimation using Swin Transformercited by 8
  6. 2024GeoReF: Geometric Alignment Across Shape Variation for Category-level Object Pose Refinementcited by 8
  7. 2022SO(3)-Pose: SO(3)-Equivariance Learning for 6D Object Pose Estimationcited by 4
  8. 2024Comparative Evaluation of 3D Reconstruction Methods for Object Pose Estimationcited by 3
  9. 2024Instance by Instance: An Iterative Framework for Multi-instance 3D Registrationcited by 2
  10. 2024Incremental Multiview Point Cloud Registration with Two-stage Candidate Retrievalcited by 2
  11. 20216D Pose Estimation with Combined Deep Learning and 3D Vision Techniques for a Fast and Accurate Object Graspingcited by 1
  12. 20226DOF Pose Estimation of a 3D Rigid Object based on Edge-enhanced Point Pair Featurescited by 0
  13. 2023GAFAR: Graph-Attention Feature-Augmentation for Registration A Fast and Light-weight Point Set Registration Algorithmcited by 0
  14. 2024Sparse Color-Code Net: Real-Time RGB-Based 6D Object Pose Estimation on Edge Devicescited by 0
  15. 2025Enhancing Transparent Object Pose Estimation: A Fusion of GDR-Net and Edge Detectioncited by 0
  16. 2026Rotational Symmetry based Object Pose Estimation from Point Clouds in the Absence of Known 3D Modelscited by 0