mlsanityData to 7 Oct 2026

fCOP: Focal Length Estimation from Category-level Object Priors

arXiv 2409.19641 ↗First posted 29 Sep 2024cs.CVcited by 1

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Abstract (arXiv)

In the realm of computer vision, the perception and reconstruction of the 3D world through vision signals heavily rely on camera intrinsic parameters, which have long been a subject of intense research within the community. In practical applications, without a strong scene geometry prior like the Manhattan World assumption or special artificial calibration patterns, monocular focal length estimation becomes a challenging task. In this paper, we propose a method for monocular focal length estimation using category-level object priors. Based on two well-studied existing tasks: monocular depth estimation and category-level object canonical representation learning, our focal solver takes depth priors and object shape priors from images containing objects and estimates the focal length from triplets of correspondences in closed form. Our experiments on simulated and real world data demonstrate that the proposed method outperforms the current state-of-the-art, offering a promising solution to the long-standing monocular focal length estimation problem.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 31 of its 41 references that are in the map. First posted on arXiv 29 Sep 2024.

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31 of 41 references.

References · 31

  1. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
  2. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,484
  3. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,346
  4. 2014Depth Map Prediction from a Single Image using a Multi-Scale Deep Networkcited by 1,264
  5. 2023ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depthcited by 646
  6. 2020AdaBins: Depth Estimation using Adaptive Binscited by 596
  7. 2019Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimationcited by 490
  8. 2024UniDepth: Universal Monocular Metric Depth Estimationcited by 375
  9. 2023Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Imagecited by 357
  10. 2023Repurposing Diffusion-Based Image Generators for Monocular Depth Estimationcited by 323
  11. 2024GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Imagecited by 283
  12. 2020TEASER: Fast and Certifiable Point Cloud Registrationcited by 274
19 more
  1. 2021FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanismcited by 121
  2. 2022GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Votingcited by 94
  3. 2022Perspective Fields for Single Image Camera Calibrationcited by 75
  4. 2021ROCA: Robust CAD Model Retrieval and Alignment from a Single Imagecited by 66
  5. 2017Guaranteed Outlier Removal for Point Cloud Registration with Correspondencescited by 62
  6. 2023SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimationcited by 52
  7. 2017A Perceptual Measure for Deep Single Image Camera Calibrationcited by 45
  8. 2024Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose Estimationcited by 41
  9. 2023IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformationcited by 40
  10. 2023VI-Net: Boosting Category-level 6D Object Pose Estimation via Learning Decoupled Rotations on the Spherical Representationscited by 40
  11. 2023Tame a Wild Camera: In-the-Wild Monocular Camera Calibrationcited by 34
  12. 2021CTRL-C: Camera calibration TRansformer with Line-Classificationcited by 33
  13. 2024DiffusionNOCS: Managing Symmetry and Uncertainty in Sim2Real Multi-Modal Category-level Pose Estimationcited by 24
  14. 2022Generative Category-Level Shape and Pose Estimation with Semantic Primitivescited by 19
  15. 2022Focal Length and Object Pose Estimation via Render and Comparecited by 17
  16. 2022ARCS: Accurate Rotation and Correspondence Searchcited by 15
  17. 2023Accelerating Globally Optimal Consensus Maximization in Geometric Visioncited by 14
  18. 2019GP2C: Geometric Projection Parameter Consensus for Joint 3D Pose and Focal Length Estimation in the Wildcited by 9
  19. 2023FocalPose++: Focal Length and Object Pose Estimation via Render and Comparecited by 3

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Citing papers per year: 2025: 1.

1 paper.

  1. 2025Relative Pose Estimation through Affine Corrections of Monocular Depth Priorscited by 18