mlsanityData to 7 Oct 2026

Category-level Object Detection, Pose Estimation and Reconstruction from Stereo Images

arXiv 2407.06984 ↗First posted 9 Jul 2024cs.CVcited by 5

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Abstract (arXiv)

We study the 3D object understanding task for manipulating everyday objects with different material properties (diffuse, specular, transparent and mixed). Existing monocular and RGB-D methods suffer from scale ambiguity due to missing or imprecise depth measurements. We present CODERS, a one-stage approach for Category-level Object Detection, pose Estimation and Reconstruction from Stereo images. The base of our pipeline is an implicit stereo matching module that combines stereo image features with 3D position information. Concatenating this presented module and the following transform-decoder architecture leads to end-to-end learning of multiple tasks required by robot manipulation. Our approach significantly outperforms all competing methods in the public TOD dataset. Furthermore, trained on simulated data, CODERS generalize well to unseen category-level object instances in real-world robot manipulation experiments. Our dataset, code, and demos will be available on our project page.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 48 of its 53 references that are in the map. First posted on arXiv 9 Jul 2024.

Builds on

48 of 53 references.

References · 48

  1. 2020End-to-End Object Detection with Transformerscited by 7,384
  2. 2017Mask R-CNNcited by 7,259
  3. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
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36 more
  1. 2021Neural Fields in Visual Computing and Beyondcited by 539
  2. 2018PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understandingcited by 521
  3. 2019Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimationcited by 490
  4. 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 324
  5. 2024TripoSR: Fast 3D Object Reconstruction from a Single Imagecited by 227
  6. 2019Meta-SR: A Magnification-Arbitrary Network for Super-Resolutioncited by 180
  7. 2020Shape Prior Deformation for Categorical 6D Object Pose and Size Estimationcited by 158
  8. 2022OnePose: One-Shot Object Pose Estimation without CAD Modelscited by 155
  9. 2022Ditto: Building Digital Twins of Articulated Objects from Interactioncited by 152
  10. 2021GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimatorcited by 148
  11. 2022GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Partscited by 135
  12. 2022Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Imagescited by 120
  13. 2023OnePose++: Keypoint-Free One-Shot Object Pose Estimation without CAD Modelscited by 114
  14. 2021Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representationscited by 107
  15. 2022GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Votingcited by 94
  16. 2021CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Cloudscited by 83
  17. 2022AKB-48: A Real-World Articulated Object Knowledge Basecited by 81
  18. 2023EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimationcited by 79
  19. 2019KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objectscited by 75
  20. 2022Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networkscited by 73
  21. 2022ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimizationcited by 70
  22. 2022CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimationcited by 69
  23. 2023CARTO: Category and Joint Agnostic Reconstruction of ARTiculated Objectscited by 64
  24. 2022Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Datasetcited by 59
  25. 2022TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and a Grasping Baselinecited by 55
  26. 2023GenPose: Generative Category-level Object Pose Estimation via Diffusion Modelscited by 47
  27. 2023IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformationcited by 40
  28. 2023TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimationcited by 32
  29. 2022Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wildcited by 22
  30. 2021SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereocited by 18
  31. 2022StereoPose: Category-Level 6D Transparent Object Pose Estimation from Stereo Images via Back-View NOCScited by 18
  32. 2023FSD: Fast Self-Supervised Single RGB-D to Categorical 3D Objectscited by 18
  33. 2021StablePose: Learning 6D Object Poses from Geometrically Stable Patchescited by 17
  34. 2022TransNet: Category-Level Transparent Object Pose Estimationcited by 13
  35. 2019Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Roboticscited by 10
  36. 2019Toward 3D Object Reconstruction from Stereo Imagescited by 2

Built on by

Cited by year (2026 to 7 Oct)

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

5 papers.

  1. 2024LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understandingcited by 17
  2. 2025CAP-Net: A Unified Network for 6D Pose and Size Estimation of Categorical Articulated Parts from a Single RGB-D Imagecited by 5
  3. 2025DeLTa: Demonstration and Language-Guided Novel Transparent Object Manipulationcited by 2
  4. 2025Beyond 'Templates': Category-Agnostic Object Pose, Size, and Shape Estimation from a Single Viewcited by 2
  5. 2026UniPR: Unified Object-level Real-to-Sim Perception and Reconstruction from a Single Stereo Paircited by 0