mlsanityData to 13 Oct 2026

Monocular Differentiable Rendering for Self-Supervised 3D Object Detection

arXiv 2009.14524 ↗First posted 30 Sep 2020cs.CV cs.LGcited by 23

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Abstract (arXiv)

3D object detection from monocular images is an ill-posed problem due to the projective entanglement of depth and scale. To overcome this ambiguity, we present a novel self-supervised method for textured 3D shape reconstruction and pose estimation of rigid objects with the help of strong shape priors and 2D instance masks. Our method predicts the 3D location and meshes of each object in an image using differentiable rendering and a self-supervised objective derived from a pretrained monocular depth estimation network. We use the KITTI 3D object detection dataset to evaluate the accuracy of the method. Experiments demonstrate that we can effectively use noisy monocular depth and differentiable rendering as an alternative to expensive 3D ground-truth labels or LiDAR information.

Key facts. Cited by 23 papers in the map (data through 13 Oct 2026). First posted on arXiv 30 Sep 2020.

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2021: 5; 2022: 11; 2023: 3; 2024: 2; 2025: 1; 2026: 1.

23 papers.

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  1. 2021DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queriescited by 658
  2. 2021Categorical Depth Distribution Network for Monocular 3D Object Detectioncited by 326
  3. 2021GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimatorcited by 148
  4. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  5. 2021GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detectioncited by 66
  6. 20223D Object Detection from Images for Autonomous Driving: A Surveycited by 66
  7. 2022Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimationcited by 34
  8. 20223D Object Detection with a Self-supervised Lidar Scene Flow Backbonecited by 19
  9. 2022Neural Groundplans: Persistent Neural Scene Representations from a Single Imagecited by 17
  10. 2024Rasterized Edge Gradients: Handling Discontinuities Differentiablycited by 14
  11. 2023NeurOCS: Neural NOCS Supervision for Monocular 3D Object Localizationcited by 13
  12. 2025Detection Based Part-level Articulated Object Reconstruction from Single RGBD Imagecited by 13
11 more
  1. 2021Stereo CenterNet based 3D Object Detection for Autonomous Drivingcited by 10
  2. 2022Baking in the Feature: Accelerating Volumetric Segmentation by Rendering Feature Mapscited by 7
  3. 2022OBMO: One Bounding Box Multiple Objects for Monocular 3D Object Detectioncited by 5
  4. 2022Physics and semantic informed multi-sensor calibration via optimization theory and self-supervised learningcited by 4
  5. 2022Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detectioncited by 3
  6. 2022Category-Level Pose Retrieval with Contrastive Features Learnt with Occlusion Augmentationcited by 2
  7. 2023M&M3D: Multi-Dataset Training and Efficient Network for Multi-view 3D Object Detectioncited by 1
  8. 2024Inverse Neural Rendering for Explainable Multi-Object Trackingcited by 1
  9. 2026MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videoscited by 1
  10. 2022Self-Supervised 3D Monocular Object Detection by Recycling Bounding Boxescited by 0
  11. 2023View-to-Label: Multi-View Consistency for Self-Supervised 3D Object Detectioncited by 0