mlsanityData to 7 Oct 2026

Generative Category-Level Shape and Pose Estimation with Semantic Primitives

arXiv 2210.01112 ↗First posted 3 Oct 2022cs.CV cs.ROcited by 19

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Abstract (arXiv)

Empowering autonomous agents with 3D understanding for daily objects is a grand challenge in robotics applications. When exploring in an unknown environment, existing methods for object pose estimation are still not satisfactory due to the diversity of object shapes. In this paper, we propose a novel framework for category-level object shape and pose estimation from a single RGB-D image. To handle the intra-category variation, we adopt a semantic primitive representation that encodes diverse shapes into a unified latent space, which is the key to establish reliable correspondences between observed point clouds and estimated shapes. Then, by using a SIM(3)-invariant shape descriptor, we gracefully decouple the shape and pose of an object, thus supporting latent shape optimization of target objects in arbitrary poses. Extensive experiments show that the proposed method achieves SOTA pose estimation performance and better generalization in the real-world dataset. Code and video are available at https://zju3dv.github.io/gCasp.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 29 of its 39 references that are in the map. First posted on arXiv 3 Oct 2022.

Builds on

29 of 39 references.

References · 29

  1. 2017Mask R-CNNcited by 7,259
  2. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  3. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  4. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 768
  5. 2022Detecting Twenty-thousand Classes using Image-level Supervisioncited by 613
  6. 2019Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimationcited by 490
  7. 2018PVNet: Pixel-wise Voting Network for 6DoF Pose Estimationcited by 385
  8. 2020INeRF: Inverting Neural Radiance Fields for Pose Estimationcited by 381
  9. 2019DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusioncited by 352
  10. 2017SSD-6D: Making RGB-based 3D detection and 6D pose estimation great againcited by 243
  11. 2019PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimationcited by 204
  12. 2021Probabilistic and Geometric Depth: Detecting Objects in Perspectivecited by 190
17 more
  1. 2020Shape Prior Deformation for Categorical 6D Object Pose and Size Estimationcited by 158
  2. 2021A System for General In-Hand Object Re-Orientationcited by 155
  3. 2020Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimationcited by 123
  4. 2021FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanismcited by 121
  5. 2021DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistencycited by 103
  6. 2019LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimationcited by 88
  7. 2020DualSDF: Semantic Shape Manipulation using a Two-Level Representationcited by 82
  8. 20196-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypointscited by 78
  9. 2018Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose Estimationcited by 74
  10. 2022ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimizationcited by 70
  11. 2022CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimationcited by 69
  12. 2020NodeSLAM: Neural Object Descriptors for Multi-View Shape Reconstructioncited by 61
  13. 2021SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimationcited by 53
  14. 2021SORNet: Spatial Object-Centric Representations for Sequential Manipulationcited by 48
  15. 2021iCaps: Iterative Category-level Object Pose and Shape Estimationcited by 23
  16. 2021Learning to Regrasp by Learning to Placecited by 11
  17. 2021ELLIPSDF: Joint Object Pose and Shape Optimization with a Bi-level Ellipsoid and Signed Distance Function Descriptioncited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 8; 2025: 2; 2026: 2.

19 papers.

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  1. 2023vMAP: Vectorised Object Mapping for Neural Field SLAMcited by 67
  2. 2023GenPose: Generative Category-level Object Pose Estimation via Diffusion Modelscited by 47
  3. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 39
  4. 2023PATS: Patch Area Transportation with Subdivision for Local Feature Matchingcited by 33
  5. 2023SOCS: Semantically-aware Object Coordinate Space for Category-Level 6D Object Pose Estimation under Large Shape Variationscited by 12
  6. 2024OV9D: Open-Vocabulary Category-Level 9D Object Pose and Size Estimationcited by 10
  7. 2024FuncGrasp: Learning Object-Centric Neural Grasp Functions from Single Annotated Example Objectcited by 6
  8. 2024ETO:Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypothesescited by 6
  9. 2023Anthropomorphic Grasping with Neural Object Shape Completioncited by 4
  10. 2023RGB-D-Based Categorical Object Pose and Shape Estimation: Methods, Datasets, and Evaluationcited by 2
  11. 2023MV-ROPE: Multi-view Constraints for Robust Category-level Object Pose and Size Estimationcited by 1
  12. 2024Diffusion-Driven Self-Supervised Learning for Shape Reconstruction and Pose Estimationcited by 1
7 more
  1. 2024ShapeICP: Iterative Category-level Object Pose and Shape Estimation from Depthcited by 1
  2. 2024fCOP: Focal Length Estimation from Category-level Object Priorscited by 1
  3. 2024Particle-based 6D Object Pose Estimation from Point Clouds using Diffusion Modelscited by 1
  4. 2025DynOPETs: A Versatile Benchmark for Dynamic Object Pose Estimation and Tracking in Moving Camera Scenarioscited by 0
  5. 2025Learning Point Cloud Representations with Pose Continuity for Depth-Based Category-Level 6D Object Pose Estimationcited by 0
  6. 2026Learning Positive-Incentive Point Sampling in Neural Implicit Fields for Object Pose Estimationcited by 0
  7. 2026ComPose: When to Trust Hands for Object Pose Trackingcited by 0