mlsanityData to 7 Oct 2026

Extending 6D Object Pose Estimators for Stereo Vision

arXiv 2402.05610 ↗First posted 8 Feb 2024cs.CV cs.AIcited by 5

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Abstract (arXiv)

Estimating the 6D pose of objects accurately, quickly, and robustly remains a difficult task. However, recent methods for directly regressing poses from RGB images using dense features have achieved state-of-the-art results. Stereo vision, which provides an additional perspective on the object, can help reduce pose ambiguity and occlusion. Moreover, stereo can directly infer the distance of an object, while mono-vision requires internalized knowledge of the object's size. To extend the state-of-the-art in 6D object pose estimation to stereo, we created a BOP compatible stereo version of the YCB-V dataset. Our method outperforms state-of-the-art 6D pose estimation algorithms by utilizing stereo vision and can easily be adopted for other dense feature-based algorithms.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 24 of its 33 references that are in the map. First posted on arXiv 8 Feb 2024.

Builds on

24 of 33 references.

References · 24

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
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  5. 2015A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimationcited by 878
  6. 2018PVNet: Pixel-wise Voting Network for 6DoF Pose Estimationcited by 385
  7. 2017End-to-End Learning of Geometry and Context for Deep Stereo Regressioncited by 359
  8. 2020CosyPose: Consistent multi-view multi-object 6D pose estimationcited by 287
  9. 2018DeepIM: Deep Iterative Matching for 6D Pose Estimationcited by 283
  10. 2018BOP: Benchmark for 6D Object Pose Estimationcited by 254
  11. 2020BOP Challenge 2020 on 6D Object Localizationcited by 192
  12. 2021GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimatorcited by 148
12 more
  1. 2015Learning to Compare Image Patches via Convolutional Neural Networkscited by 109
  2. 2020HybridPose: 6D Object Pose Estimation under Hybrid Representationscited by 107
  3. 2018SegStereo: Exploiting Semantic Information for Disparity Estimationcited by 88
  4. 2021SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimationcited by 88
  5. 2021MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matchingcited by 82
  6. 2019KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objectscited by 75
  7. 2014Computing the Stereo Matching Cost with a Convolutional Neural Networkcited by 74
  8. 2023BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objectscited by 70
  9. 2021RePOSE: Fast 6D Object Pose Refinement via Deep Texture Renderingcited by 63
  10. 2022Coupled Iterative Refinement for 6D Multi-Object Pose Estimationcited by 48
  11. 2021StereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimationcited by 40
  12. 2019AMNet: Deep Atrous Multiscale Stereo Disparity Estimation Networkscited by 7

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 1; 2026: 1.

5 papers.

  1. 2024End-to-End Probabilistic Geometry-Guided Regression for 6DoF Object Pose Estimationcited by 2
  2. 2024FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimationcited by 0
  3. 2024YCB-LUMA: YCB Object Dataset with Luminance Keying for Object Localizationcited by 0
  4. 2025Improving 6D Object Pose Estimation of metallic Household and Industry Objectscited by 0
  5. 2026Keypoint-based Dynamic Object 6-DoF Pose Tracking via Event Cameracited by 0