mlsanityData to 14 Oct 2026

RYOPO: Bringing End-to-End Category-Level Object Pose Estimation into Real Time

arXiv 2610.03013 ↗First posted 2 Oct 2026cs.CV cs.ROcited by 0

Not on the map. Why?

Abstract (arXiv)

Category-level object pose estimation predicts the rotation, translation, and metric size of unseen instances within known categories. Many accurate RGB-D methods rely on external instance segmentation and crop-based pose estimation, introducing separate stages and object-dependent processing costs that hinder real-time inference. To bring accurate pose estimation into real time, we present ours, an end-to-end trainable query-based RGB-D set predictor. It jointly detects and segments objects and estimates their mbox9-DoF poses without explicit CAD-derived shape priors or a separately trained instance segmentor. Shared image and scene encoding avoids repeated per-object crop encoding. A query-conditioned geometry pathway associates observed 3D points and RGB features with object queries and incorporates shared scene context. Object-centric refinement uses the resulting point descriptors to update an explicit pose state through pose-conditioned cross-attention and recurrent residual corrections. On NOCS, ours substantially improves on published RGB-D joint detection and pose estimation results. It achieves competitive performance compared with two-stage methods under all-object evaluation on REAL275 and HouseCat6D, while enabling real-time full-frame pose estimation at 31.8 FPS on an RTX~A6000. Project page: https://yopo-series.github.io/RYOPO-project-page/.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 38 of its 41 references that are in the map. First posted on arXiv 2 Oct 2026.

Builds on

38 of 41 references.

References · 38

  1. 2020End-to-End Object Detection with Transformerscited by 7,414
  2. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  3. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
  4. 2022DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detectioncited by 1,319
  5. 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,214
  6. 20173D Semantic Segmentation with Submanifold Sparse Convolutional Networkscited by 748
  7. 2021DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queriescited by 658
  8. 2022PETR: Position Embedding Transformation for Multi-View 3D Object Detectioncited by 552
  9. 2023DETRs Beat YOLOs on Real-time Object Detectioncited by 533
  10. 2019Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimationcited by 495
  11. 2019DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusioncited by 355
  12. 2022Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentationcited by 344
26 more
  1. 2019MVX-Net: Multimodal VoxelNet for 3D Object Detectioncited by 163
  2. 2020Shape Prior Deformation for Categorical 6D Object Pose and Size Estimationcited by 161
  3. 2022Multimodal Token Fusion for Vision Transformerscited by 136
  4. 2024RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformercited by 91
  5. 2022Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networkscited by 74
  6. 2022ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimizationcited by 72
  7. 2022CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimationcited by 70
  8. 2023Cross Modal Transformer: Towards Fast and Robust 3D Object Detectioncited by 70
  9. 2022HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarioscited by 53
  10. 2023SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimationcited by 53
  11. 2023HS-Pose: Hybrid Scope Feature Extraction for Category-level Object Pose Estimationcited by 49
  12. 2024Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose Estimationcited by 43
  13. 2023VI-Net: Boosting Category-level 6D Object Pose Estimation via Learning Decoupled Rotations on the Spherical Representationscited by 41
  14. 2023V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detectioncited by 35
  15. 2024RT-DETRv3: Real-time End-to-End Object Detection with Hierarchical Dense Positive Supervisioncited by 32
  16. 2022CATRE: Iterative Point Clouds Alignment for Category-level Object Pose Refinementcited by 29
  17. 2023Uni3DETR: Unified 3D Detection Transformercited by 27
  18. 2022Bridged Transformer for Vision and Point Cloud 3D Object Detectioncited by 20
  19. 2023FSD: Fast Self-Supervised Single RGB-D to Categorical 3D Objectscited by 19
  20. 2025GCE-Pose: Global Context Enhancement for Category-level Object Pose Estimationcited by 18
  21. 2025RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Modelscited by 15
  22. 2025CleanPose: Category-Level Object Pose Estimation via Causal Learning and Knowledge Distillationcited by 10
  23. 2023Real-time Simultaneous Multi-Object 3D Shape Reconstruction, 6DoF Pose Estimation and Dense Grasp Predictioncited by 3
  24. 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
  25. 2025You Only Pose Once: A Minimalist's Detection Transformer for Monocular RGB Category-level 9D Multi-Object Pose Estimationcited by 3
  26. 2026EdgeCrafter: Compact ViTs for Edge Dense Prediction via Task-Specialized Distillationcited by 3

Built on by

Not cited yet.