mlsanityData to 14 Oct 2026

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes

arXiv 2607.23669 ↗First posted 26 Jul 2026cs.CV cs.ROcited by 0

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Abstract (arXiv)

Robust object 6D pose tracking is critical for robotic systems operating in dynamic and occluded scenes. Per-frame estimators are accurate but computationally expensive, while current trackers struggle with fast motion and complete occlusion due to their reliance on continuous visibility. To address these challenges, we present RRTrack, an efficient, recoverable object 6D pose tracker that enables robust tracking through fast motion and target disappearance--reappearance. RRTrack introduces a 2D--6D closed-loop tracking strategy that integrates memory-based video object segmentation (VOS) with 6D pose refinement. The 2D branch maintains target localization, and the 6D branch verifies geometric consistency before memory updates. In addition, a DINOv2-based dual-bank template matching module is developed to recover lost targets by jointly exploiting offline synthetic templates and online observation anchors while maintaining real-time efficiency. We also introduce a synthetic RGB-D benchmark comprising three robotic scenarios with fast motion and full occlusion. Experimental results on the synthetic benchmark demonstrate that RRTrack improves equal-subset mean ADD-S AR by 66.3% and ADD-S AUC by 65.7% over FoundationPose while achieving 55.2 FPS. Real-world experiments further validate the robustness of RRTrack under noisy sensing conditions. Project page: https://github.com/7kevin24/RRTrack

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 31 of its 37 references that are in the map. First posted on arXiv 26 Jul 2026.

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31 of 37 references.

References · 31

  1. 2023Segment Anythingcited by 8,234
  2. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  3. 2024SAM 2: Segment Anything in Images and Videoscited by 2,863
  4. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
  5. 2023FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objectscited by 429
  6. 2022Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Frameworkcited by 330
  7. 2018DeepIM: Deep Iterative Matching for 6D Pose Estimationcited by 283
  8. 2018BOP: Benchmark for 6D Object Pose Estimationcited by 254
  9. 2022MegaPose: 6D Pose Estimation of Novel Objects via Render & Comparecited by 201
  10. 2023Putting the Object Back into Video Object Segmentationcited by 188
  11. 2023SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimationcited by 117
  12. 2023GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondencecited by 114
19 more
  1. 2023FoundPose: Unseen Object Pose Estimation with Foundation Featurescited by 109
  2. 2019PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Trackingcited by 91
  3. 2021BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Modelscited by 87
  4. 2023CNOS: A Strong Baseline for CAD-based Novel Object Segmentationcited by 87
  5. 2023FreeZe: Training-free zero-shot 6D pose estimation with geometric and vision foundation modelscited by 57
  6. 2024AI Flow at the Network Edgecited by 46
  7. 2023ZS6D: Zero-shot 6D Object Pose Estimation using Vision Transformerscited by 45
  8. 2025AI Flow: Perspectives, Scenarios, and Approachescited by 44
  9. 2022OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimationcited by 43
  10. 2021Learning general and distinctive 3D local deep descriptors for point cloud registrationcited by 42
  11. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 40
  12. 2024GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objectscited by 33
  13. 2022Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objectscited by 30
  14. 2021ZePHyR: Zero-shot Pose Hypothesis Ratingcited by 26
  15. 2024Object Pose Estimation via the Aggregation of Diffusion Featurescited by 12
  16. 2025RGBTrack: Fast, Robust Depth-Free 6D Pose Estimation and Trackingcited by 6
  17. 2025DynamicPose: Real-time and Robust 6D Object Pose Tracking for Fast-Moving Cameras and Objectscited by 5
  18. 2024Diffusion Features for Zero-Shot 6DoF Object Pose Estimationcited by 4
  19. 2026Generative Transmission: Rethinking Computation, Bandwidth, and Memory in Communicationcited by 2

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