mlsanityData to 7 Oct 2026

DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion

arXiv 1902.00761 ↗First posted 2 Feb 2019cs.CVcited by 38

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Abstract (arXiv)

In this paper we propose a convolutional neural network that is designed to upsample a series of sparse range measurements based on the contextual cues gleaned from a high resolution intensity image. Our approach draws inspiration from related work on super-resolution and in-painting. We propose a novel architecture that seeks to pull contextual cues separately from the intensity image and the depth features and then fuse them later in the network. We argue that this approach effectively exploits the relationship between the two modalities and produces accurate results while respecting salient image structures. We present experimental results to demonstrate that our approach is comparable with state of the art methods and generalizes well across multiple datasets.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Feb 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 8; 2022: 8; 2023: 7; 2024: 7; 2025: 7; 2026: 1.

38 papers.

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  1. 2021Unsupervised Depth Completion with Calibrated Backprojection Layerscited by 61
  2. 2021Learning Topology from Synthetic Data for Unsupervised Depth Completioncited by 38
  3. 2022Deep Depth Completion from Extremely Sparse Data: A Surveycited by 33
  4. 2021An Adaptive Framework for Learning Unsupervised Depth Completioncited by 30
  5. 2022DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completioncited by 27
  6. 2024Test-Time Adaptation for Depth Completioncited by 26
  7. 2022Monitored Distillation for Positive Congruent Depth Completioncited by 24
  8. 2023AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimationcited by 15
  9. 2022Depth Completion using Geometry-Aware Embeddingcited by 12
  10. 2024Completion as Enhancement: A Degradation-Aware Selective Image Guided Network for Depth Completioncited by 12
  11. 2025ProtoDepth: Unsupervised Continual Depth Completion with Prototypescited by 11
  12. 2021S3: Learnable Sparse Signal Superdensity for Guided Depth Estimationcited by 10
26 more
  1. 2023AGG-Net: Attention Guided Gated-convolutional Network for Depth Image Completioncited by 8
  2. 2024RGB Guided ToF Imaging System: A Survey of Deep Learning-based Methodscited by 8
  3. 2024All-day Depth Completioncited by 8
  4. 2022A Low Memory Footprint Quantized Neural Network for Depth Completion of Very Sparse Time-of-Flight Depth Mapscited by 6
  5. 2021PDC: Piecewise Depth Completion utilizing Superpixelscited by 5
  6. 2024UnCLe: Benchmarking Unsupervised Continual Learning for Depth Completioncited by 5
  7. 2023Revisiting Deformable Convolution for Depth Completioncited by 4
  8. 2024Stereo-LiDAR Depth Estimation with Deformable Propagation and Learned Disparity-Depth Conversioncited by 4
  9. 2025A Review of 3D Object Detection with Vision-Language Modelscited by 4
  10. 2025ETA: Energy-based Test-time Adaptation for Depth Completioncited by 4
  11. 2021DVMN: Dense Validity Mask Network for Depth Completioncited by 3
  12. 2021Adaptive Illumination based Depth Sensing using Deep Superpixel and Soft Sampling Approximationcited by 2
  13. 2022How to Guide Adaptive Depth Sampling?cited by 2
  14. 2023Gated Cross-Attention Network for Depth Completioncited by 2
  15. 2021Self-Guided Instance-Aware Network for Depth Completion and Enhancementcited by 1
  16. 2022Non-learning Stereo-aided Depth Completion under Mis-projection via Selective Stereo Matchingcited by 1
  17. 2025StarryGazer: Leveraging Monocular Depth Estimation Models for Domain-Agnostic Single Depth Image Completioncited by 1
  18. 2022MetaComp: Learning to Adapt for Online Depth Completioncited by 0
  19. 2023Sparse Depth-Guided Attention for Accurate Depth Completion: A Stereo-Assisted Monitored Distillation Approachcited by 0
  20. 2023DEUX: Active Exploration for Learning Unsupervised Depth Perceptioncited by 0
  21. 2023Self-Supervised Depth Completion Guided by 3D Perception and Geometry Consistencycited by 0
  22. 2024Mask-adaptive Gated Convolution and Bi-directional Progressive Fusion Network for Depth Completioncited by 0
  23. 2025Preserving Guidance in Cost-Volume Retrieval under Extreme LiDAR Sparsity in Iterative Stereocited by 0
  24. 2025S2ML: Spatio-Spectral Mutual Learning for Depth Completioncited by 0
  25. 2025MT-Depth: Multi-task Instance feature analysis for the Depth Completioncited by 0
  26. 2026Depth-to-Image Synthesis-Driven Generative Unguided Depth Completioncited by 0