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Dense Depth Posterior (DDP) from Single Image and Sparse Range

arXiv 1901.10034 ↗First posted 28 Jan 2019cs.CVcited by 57

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Abstract (arXiv)

We present a deep learning system to infer the posterior distribution of a dense depth map associated with an image, by exploiting sparse range measurements, for instance from a lidar. While the lidar may provide a depth value for a small percentage of the pixels, we exploit regularities reflected in the training set to complete the map so as to have a probability over depth for each pixel in the image. We exploit a Conditional Prior Network, that allows associating a probability to each depth value given an image, and combine it with a likelihood term that uses the sparse measurements. Optionally we can also exploit the availability of stereo during training, but in any case only require a single image and a sparse point cloud at run-time. We test our approach on both unsupervised and supervised depth completion using the KITTI benchmark, and improve the state-of-the-art in both.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jan 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 11; 2022: 16; 2023: 8; 2024: 13; 2025: 8; 2026: 1.

57 papers.

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  1. 2021RigNet: Repetitive Image Guided Network for Depth Completioncited by 80
  2. 2021Unsupervised Depth Completion with Calibrated Backprojection Layerscited by 61
  3. 2024Bilateral Propagation Network for Depth Completioncited by 59
  4. 2021Depth Completion with Twin Surface Extrapolation at Occlusion Boundariescited by 41
  5. 2021Learning Topology from Synthetic Data for Unsupervised Depth Completioncited by 38
  6. 2024WorDepth: Variational Language Prior for Monocular Depth Estimationcited by 34
  7. 2022Deep Depth Completion from Extremely Sparse Data: A Surveycited by 33
  8. 2022Not Just Streaks: Towards Ground Truth for Single Image Derainingcited by 31
  9. 2021An Adaptive Framework for Learning Unsupervised Depth Completioncited by 30
  10. 2022DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completioncited by 27
  11. 2024Test-Time Adaptation for Depth Completioncited by 26
  12. 2022Monitored Distillation for Positive Congruent Depth Completioncited by 24
38 more
  1. 2021Bayesian Deep Basis Fitting for Depth Completion with Uncertaintycited by 23
  2. 2022ALTO: Alternating Latent Topologies for Implicit 3D Reconstructioncited by 21
  3. 2024RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric Scalecited by 20
  4. 2024RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptionscited by 20
  5. 2021A Surface Geometry Model for LiDAR Depth Completioncited by 18
  6. 2021Stereoscopic Universal Perturbations across Different Architectures and Datasetscited by 17
  7. 2023AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimationcited by 15
  8. 2021Advancing Self-supervised Monocular Depth Learning with Sparse LiDARcited by 13
  9. 2024Completion as Enhancement: A Degradation-Aware Selective Image Guided Network for Depth Completioncited by 12
  10. 2022Towards 3D Scene Reconstruction from Locally Scale-Aligned Monocular Video Depthcited by 11
  11. 2023RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completioncited by 11
  12. 2025ProtoDepth: Unsupervised Continual Depth Completion with Prototypescited by 11
  13. 2023Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedbackcited by 10
  14. 2024Distilling Diffusion Models to Efficient 3D LiDAR Scene Completioncited by 10
  15. 2022Simultaneous Acquisition of High Quality RGB Image and Polarization Information using a Sparse Polarization Sensorcited by 9
  16. 2023Clutter Detection and Removal in 3D Scenes with View-Consistent Inpaintingcited by 9
  17. 2025Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokenscited by 9
  18. 2024RGB Guided ToF Imaging System: A Survey of Deep Learning-based Methodscited by 8
  19. 2024All-day Depth Completioncited by 8
  20. 2024GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsamplingcited by 7
  21. 2022A Low Memory Footprint Quantized Neural Network for Depth Completion of Very Sparse Time-of-Flight Depth Mapscited by 6
  22. 2022Towards Domain-agnostic Depth Completioncited by 6
  23. 2022Learning an Efficient Multimodal Depth Completion Modelcited by 6
  24. 2021DnD: Dense Depth Estimation in Crowded Dynamic Indoor Scenescited by 5
  25. 2022SemSegDepth: A Combined Model for Semantic Segmentation and Depth Completioncited by 5
  26. 2024UnCLe: Benchmarking Unsupervised Continual Learning for Depth Completioncited by 5
  27. 2025Radar-Guided Polynomial Fitting for Metric Depth Estimationcited by 5
  28. 2025Diffusion Distillation With Direct Preference Optimization For Efficient 3D LiDAR Scene Completioncited by 4
  29. 2025ETA: Energy-based Test-time Adaptation for Depth Completioncited by 4
  30. 2021Adaptive Illumination based Depth Sensing using Deep Superpixel and Soft Sampling Approximationcited by 2
  31. 2022Segmentation-guided Domain Adaptation for Efficient Depth Completioncited by 2
  32. 2022PanDepth: Joint Panoptic Segmentation and Depth Completioncited by 2
  33. 2022Non-learning Stereo-aided Depth Completion under Mis-projection via Selective Stereo Matchingcited by 1
  34. 2023Lidar Line Selection with Spatially-Aware Shapley Value for Cost-Efficient Depth Completioncited by 1
  35. 2025DenseFormer: Learning Dense Depth Map from Sparse Depth and Image via Conditional Diffusion Modelcited by 1
  36. 2025StarryGazer: Leveraging Monocular Depth Estimation Models for Domain-Agnostic Single Depth Image Completioncited by 1
  37. 2022On the Viability of Monocular Depth Pre-training for Semantic Segmentationcited by 0
  38. 2022MetaComp: Learning to Adapt for Online Depth Completioncited by 0

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