mlsanityData to 7 Oct 2026

MonoEdge: Monocular 3D Object Detection Using Local Perspectives

arXiv 2301.01802 ↗First posted 4 Jan 2023cs.CV cs.AIcited by 6

Not on the map. Why?

Abstract (arXiv)

We propose a novel approach for monocular 3D object detection by leveraging local perspective effects of each object. While the global perspective effect shown as size and position variations has been exploited for monocular 3D detection extensively, the local perspectives has long been overlooked. We design a local perspective module to regress a newly defined variable named keyedge-ratios as the parameterization of the local shape distortion to account for the local perspective, and derive the object depth and yaw angle from it. Theoretically, this module does not rely on the pixel-wise size or position in the image of the objects, therefore independent of the camera intrinsic parameters. By plugging this module in existing monocular 3D object detection frameworks, we incorporate the local perspective distortion with global perspective effect for monocular 3D reasoning, and we demonstrate the effectiveness and superior performance over strong baseline methods in multiple datasets.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 32 of its 39 references that are in the map. First posted on arXiv 4 Jan 2023.

Builds on

32 of 39 references.

References · 32

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20 more
  1. 2021Objects are Different: Flexible Monocular 3D Object Detectioncited by 184
  2. 2019Learning Depth-Guided Convolutions for Monocular 3D Object Detectioncited by 169
  3. 2021Geometry Uncertainty Projection Network for Monocular 3D Object Detectioncited by 155
  4. 2020MonoPair: Monocular 3D Object Detection Using Pairwise Spatial Relationshipscited by 153
  5. 2020RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Drivingcited by 150
  6. 2021Delving into Localization Errors for Monocular 3D Object Detectioncited by 138
  7. 2018ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shapecited by 123
  8. 2019GS3D: An Efficient 3D Object Detection Framework for Autonomous Drivingcited by 106
  9. 2019Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstructioncited by 106
  10. 2021AutoShape: Real-Time Shape-Aware Monocular 3D Object Detectioncited by 87
  11. 2021Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detectioncited by 84
  12. 2021Geometry-based Distance Decomposition for Monocular 3D Object Detectioncited by 83
  13. 2019How do neural networks see depth in single images?cited by 82
  14. 2021MonoRUn: Monocular 3D Object Detection by Reconstruction and Uncertainty Propagationcited by 82
  15. 2019CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depthcited by 75
  16. 2021Monocular 3D Object Detection: An Extrinsic Parameter Free Approachcited by 69
  17. 2021Ground-aware Monocular 3D Object Detection for Autonomous Drivingcited by 65
  18. 2019Towards Generalization Across Depth for Monocular 3D Object Detectioncited by 41
  19. 2021Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object Detectioncited by 20
  20. 2020Exploring intermediate representation for monocular vehicle pose estimationcited by 12

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 4; 2025: 1.

6 papers.

  1. 2024OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Drivingcited by 93
  2. 2024MonoCD: Monocular 3D Object Detection with Complementary Depthscited by 38
  3. 2024MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error Priorscited by 21
  4. 2023SSD-MonoDETR: Supervised Scale-aware Deformable Transformer for Monocular 3D Object Detectioncited by 9
  5. 2025StereoDETR: Stereo-based Transformer for 3D Object Detectioncited by 2
  6. 2024Efficient Feature Aggregation and Scale-Aware Regression for Monocular 3D Object Detectioncited by 0