mlsanityData to 14 Oct 2026

Diffusion Features for Zero-Shot 6DoF Object Pose Estimation

arXiv 2411.16668 ↗First posted 25 Nov 2024cs.CVcited by 4

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Abstract (arXiv)

Zero-shot object pose estimation enables the retrieval of object poses from images without necessitating object-specific training. In recent approaches this is facilitated by vision foundation models (VFM), which are pre-trained models that are effectively general-purpose feature extractors. The characteristics exhibited by these VFMs vary depending on the training data, network architecture, and training paradigm. The prevailing choice in this field are self-supervised Vision Transformers (ViT). This study assesses the influence of Latent Diffusion Model (LDM) backbones on zero-shot pose estimation. In order to facilitate a comparison between the two families of models on a common ground we adopt and modify a recent approach. Therefore, a template-based multi-staged method for estimating poses in a zero-shot fashion using LDMs is presented. The efficacy of the proposed approach is empirically evaluated on three standard datasets for object-specific 6DoF pose estimation. The experiments demonstrate an Average Recall improvement of up to 27% over the ViT baseline. The source code is available at: https://github.com/BvG1993/DZOP.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 47 of its 63 references that are in the map. First posted on arXiv 25 Nov 2024.

Builds on

47 of 63 references.

References · 47

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35 more
  1. 2019Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimationcited by 495
  2. 2023FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objectscited by 429
  3. 2023A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondencecited by 301
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  5. 2020CosyPose: Consistent multi-view multi-object 6D pose estimationcited by 287
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  11. 2017T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objectscited by 210
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  13. 2022MegaPose: 6D Pose Estimation of Novel Objects via Render & Comparecited by 201
  14. 2023On the Importance of Noise Scheduling for Diffusion Modelscited by 194
  15. 2021GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimatorcited by 148
  16. 2023SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimationcited by 117
  17. 2023GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondencecited by 114
  18. 2023FoundPose: Unseen Object Pose Estimation with Foundation Featurescited by 109
  19. 2022GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Votingcited by 94
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  24. 2022Zero-Shot Category-Level Object Pose Estimationcited by 57
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Built on by

Cited by year (2026 to 14 Oct)

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

4 papers.

  1. 2025Accurate and efficient zero-shot 6D pose estimation with frozen foundation modelscited by 13
  2. 2025Color-Pair Guided Robust Zero-Shot 6D Pose Estimation and Tracking of Cluttered Objects on Edge Devicescited by 0
  3. 2025Geo6DPose: Fast Zero-Shot 6D Object Pose Estimation via Geometry-Filtered Feature Matchingcited by 0
  4. 2026RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025HIPPo: Harnessing Image-to-3D Priors for Model-free Zero-shot 6D Pose Estimation
  2. 2024Category Level 6D Object Pose Estimation from a Single RGB Image using Diffusion
  3. 2025Zero-shot Human Pose Estimation using Diffusion-based Inverse solvers
  4. 2025Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation
  5. 2022Few-Shot Diffusion Models
  6. 2025Joint Learning of Pose Regression and Denoising Diffusion with Score Scaling Sampling for Category-level 6D Pose Estimation
  7. 2025Studying Image Diffusion Features for Zero-Shot Video Object Segmentation
  8. 2022DiffPose: Multi-hypothesis Human Pose Estimation using Diffusion models