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Category Level Object Pose Estimation via Neural Analysis-by-Synthesis

arXiv 2008.08145 ↗First posted 18 Aug 2020cs.CVcited by 100

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Abstract (arXiv)

Many object pose estimation algorithms rely on the analysis-by-synthesis framework which requires explicit representations of individual object instances. In this paper we combine a gradient-based fitting procedure with a parametric neural image synthesis module that is capable of implicitly representing the appearance, shape and pose of entire object categories, thus rendering the need for explicit CAD models per object instance unnecessary. The image synthesis network is designed to efficiently span the pose configuration space so that model capacity can be used to capture the shape and local appearance (i.e., texture) variations jointly. At inference time the synthesized images are compared to the target via an appearance based loss and the error signal is backpropagated through the network to the input parameters. Keeping the network parameters fixed, this allows for iterative optimization of the object pose, shape and appearance in a joint manner and we experimentally show that the method can recover orientation of objects with high accuracy from 2D images alone. When provided with depth measurements, to overcome scale ambiguities, the method can accurately recover the full 6DOF pose successfully.

Key facts. Cited by 100 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Aug 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 16; 2022: 27; 2023: 22; 2024: 20; 2025: 10; 2026: 5.

100 papers.

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  1. 2022MegaPose: 6D Pose Estimation of Novel Objects via Render & Comparecited by 198
  2. 2022OnePose: One-Shot Object Pose Estimation without CAD Modelscited by 155
  3. 2024HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splattingcited by 141
  4. 2022Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Imagescited by 120
  5. 2023OnePose++: Keypoint-Free One-Shot Object Pose Estimation without CAD Modelscited by 114
  6. 2023GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondencecited by 113
  7. 2024RGBD Objects in the Wild: Scaling Real-World 3D Object Learning from RGB-D Videoscited by 113
  8. 2021DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistencycited by 103
  9. 2021BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Modelscited by 87
  10. 2024HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Drivingcited by 84
  11. 2021CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Cloudscited by 83
  12. 2022OSOP: A Multi-Stage One Shot Object Pose Estimation Frameworkcited by 81
38 more
  1. 2023HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Videocited by 76
  2. 2022gDNA: Towards Generative Detailed Neural Avatarscited by 72
  3. 2022ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimizationcited by 70
  4. 2021Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networkscited by 69
  5. 2022CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimationcited by 69
  6. 2022Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Datasetcited by 59
  7. 2022Zero-Shot Category-Level Object Pose Estimationcited by 57
  8. 2021Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimationcited by 45
  9. 2022OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimationcited by 43
  10. 2021Single-Stage Keypoint-Based Category-Level Object Pose Estimation from an RGB Imagecited by 42
  11. 2021NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimationcited by 41
  12. 2021Category-Level Metric Scale Object Shape and Pose Estimationcited by 40
  13. 2023IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformationcited by 40
  14. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 39
  15. 2024GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objectscited by 32
  16. 2021Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overviewcited by 31
  17. 2023POPE: 6-DoF Promptable Pose Estimation of Any Object, in Any Scene, with One Referencecited by 30
  18. 2022Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Imagecited by 29
  19. 2022CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wildcited by 28
  20. 2021UDA-COPE: Unsupervised Domain Adaptation for Category-level Object Pose Estimationcited by 25
  21. 2024DiffusionNOCS: Managing Symmetry and Uncertainty in Sim2Real Multi-Modal Category-level Pose Estimationcited by 24
  22. 2021iCaps: Iterative Category-level Object Pose and Shape Estimationcited by 23
  23. 2022Robust Category-Level 6D Pose Estimation with Coarse-to-Fine Rendering of Neural Featurescited by 23
  24. 2022TexPose: Neural Texture Learning for Self-Supervised 6D Object Pose Estimationcited by 23
  25. 2022Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wildcited by 22
  26. 2023Challenges for Monocular 6D Object Pose Estimation in Roboticscited by 21
  27. 20216D-ViT: Category-Level 6D Object Pose Estimation via Transformer-based Instance Representation Learningcited by 20
  28. 2021Mending Neural Implicit Modeling for 3D Vehicle Reconstruction in the Wildcited by 19
  29. 2022Keypoint-Based Category-Level Object Pose Tracking from an RGB Sequence with Uncertainty Estimationcited by 19
  30. 2023Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Imagescited by 18
  31. 2022Tracking and Reconstructing Hand Object Interactions from Point Cloud Sequences in the Wildcited by 17
  32. 2022PIZZA: A Powerful Image-only Zero-Shot Zero-CAD Approach to 6 DoF Trackingcited by 15
  33. 2023iFusion: Inverting Diffusion for Pose-Free Reconstruction from Sparse Viewscited by 14
  34. 2024GS-Pose: Generalizable Segmentation-based 6D Object Pose Estimation with 3D Gaussian Splattingcited by 14
  35. 2023RGB-based Category-level Object Pose Estimation via Decoupled Metric Scale Recoverycited by 13
  36. 2024LaPose: Laplacian Mixture Shape Modeling for RGB-Based Category-Level Object Pose Estimationcited by 13
  37. 2025Orientation Matters: Making 3D Generative Models Orientation-Alignedcited by 13
  38. 2021DISP6D: Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimationcited by 12

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