mlsanityData to 13 Oct 2026

Deep MANTA: A Coarse-to-fine Many-Task Network for joint 2D and 3D vehicle analysis from monocular image

arXiv 1703.07570 ↗First posted 22 Mar 2017cs.CVcited by 95

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Abstract (arXiv)

In this paper, we present a novel approach, called Deep MANTA (Deep Many-Tasks), for many-task vehicle analysis from a given image. A robust convolutional network is introduced for simultaneous vehicle detection, part localization, visibility characterization and 3D dimension estimation. Its architecture is based on a new coarse-to-fine object proposal that boosts the vehicle detection. Moreover, the Deep MANTA network is able to localize vehicle parts even if these parts are not visible. In the inference, the network's outputs are used by a real time robust pose estimation algorithm for fine orientation estimation and 3D vehicle localization. We show in experiments that our method outperforms monocular state-of-the-art approaches on vehicle detection, orientation and 3D location tasks on the very challenging KITTI benchmark.

Key facts. Cited by 95 papers in the map (data through 13 Oct 2026). First posted on arXiv 22 Mar 2017.

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2021: 38; 2022: 25; 2023: 21; 2024: 4; 2025: 4; 2026: 3.

95 papers.

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  1. 2021Categorical Depth Distribution Network for Monocular 3D Object Detectioncited by 326
  2. 2021Is Pseudo-Lidar needed for Monocular 3D Object detection?cited by 248
  3. 2021PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detectioncited by 232
  4. 2021Objects are Different: Flexible Monocular 3D Object Detectioncited by 184
  5. 2021ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detectioncited by 157
  6. 2021Geometry Uncertainty Projection Network for Monocular 3D Object Detectioncited by 155
  7. 2021Delving into Localization Errors for Monocular 3D Object Detectioncited by 139
  8. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  9. 20213D Object Detection for Autonomous Driving: A Surveycited by 106
  10. 2021AutoShape: Real-Time Shape-Aware Monocular 3D Object Detectioncited by 87
  11. 2021MonoRUn: Monocular 3D Object Detection by Reconstruction and Uncertainty Propagationcited by 82
  12. 2021Monocular Quasi-Dense 3D Object Trackingcited by 80
38 more
  1. 2023EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimationcited by 79
  2. 2021Monocular 3D Object Detection: An Extrinsic Parameter Free Approachcited by 69
  3. 2021Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detectioncited by 66
  4. 20223D Object Detection from Images for Autonomous Driving: A Surveycited by 66
  5. 2022DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detectioncited by 48
  6. 2021M3DSSD: Monocular 3D Single Stage Object Detectorcited by 39
  7. 2022MonoGround: Detecting Monocular 3D Objects from the Groundcited by 37
  8. 2023Diversifying the High-level Features for better Adversarial Transferabilitycited by 34
  9. 2023MonoNeRD: NeRF-like Representations for Monocular 3D Object Detectioncited by 33
  10. 2022CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detectioncited by 32
  11. 2022Pseudo-Stereo for Monocular 3D Object Detection in Autonomous Drivingcited by 30
  12. 2024Vision-based 3D occupancy prediction in autonomous driving: a review and outlookcited by 29
  13. 2023WEDGE: A multi-weather autonomous driving dataset built from generative vision-language modelscited by 28
  14. 2022Densely Constrained Depth Estimator for Monocular 3D Object Detectioncited by 27
  15. 2023CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulationcited by 26
  16. 2022Homography Loss for Monocular 3D Object Detectioncited by 24
  17. 2022OPA-3D: Occlusion-Aware Pixel-Wise Aggregation for Monocular 3D Object Detectioncited by 23
  18. 2023Object Detection with Transformers: A Reviewcited by 22
  19. 2021Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homographycited by 21
  20. 2021MonoGRNet: A General Framework for Monocular 3D Object Detectioncited by 20
  21. 2021Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object Detectioncited by 20
  22. 2021Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Imagecited by 20
  23. 2023MonoGAE: Roadside Monocular 3D Object Detection with Ground-Aware Embeddingscited by 20
  24. 2021PLUMENet: Efficient 3D Object Detection from Stereo Imagescited by 19
  25. 2023MonoATT: Online Monocular 3D Object Detection with Adaptive Token Transformercited by 18
  26. 2023Viewpoint Equivariance for Multi-View 3D Object Detectioncited by 18
  27. 2021MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentationcited by 16
  28. 2021Optimal Pose and Shape Estimation for Category-level 3D Object Perceptioncited by 15
  29. 2023NeurOCS: Neural NOCS Supervision for Monocular 3D Object Localizationcited by 13
  30. 2021SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimationcited by 12
  31. 2024SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objectscited by 12
  32. 2021Weakly Supervised Training of Monocular 3D Object Detectors Using Wide Baseline Multi-view Traffic Camera Datacited by 11
  33. 2022HFT: Lifting Perspective Representations via Hybrid Feature Transformationcited by 11
  34. 2022Multi-Sem Fusion: Multimodal Semantic Fusion for 3D Object Detectioncited by 11
  35. 2021Lite-FPN for Keypoint-based Monocular 3D Object Detectioncited by 10
  36. 2023MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimationcited by 9
  37. 2025Unleashing the Power of Chain-of-Prediction for Monocular 3D Object Detectioncited by 9
  38. 2021Know Your Surroundings: Panoramic Multi-Object Tracking by Multimodality Collaborationcited by 8

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