mlsanityData to 7 Oct 2026

Deep Learning-based Depth Estimation Methods from Monocular Image and Videos: A Comprehensive Survey

arXiv 2406.19675 ↗First posted 28 Jun 2024cs.CVcited by 15

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Abstract (arXiv)

Estimating depth from single RGB images and videos is of widespread interest due to its applications in many areas, including autonomous driving, 3D reconstruction, digital entertainment, and robotics. More than 500 deep learning-based papers have been published in the past 10 years, which indicates the growing interest in the task. This paper presents a comprehensive survey of the existing deep learning-based methods, the challenges they address, and how they have evolved in their architecture and supervision methods. It provides a taxonomy for classifying the current work based on their input and output modalities, network architectures, and learning methods. It also discusses the major milestones in the history of monocular depth estimation, and different pipelines, datasets, and evaluation metrics used in existing methods.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 112 of its 194 references that are in the map. First posted on arXiv 28 Jun 2024.

Builds on

112 of 194 references.

References · 112

  1. 2023Segment Anythingcited by 8,158
  2. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
  3. 2018CBAM: Convolutional Block Attention Modulecited by 2,463
  4. 2021Vision Transformers for Dense Predictioncited by 1,789
  5. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,484
  6. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,346
  7. 2014Depth Map Prediction from a Single Image using a Multi-Scale Deep Networkcited by 1,264
  8. 2021Transformers in Vision: A Surveycited by 1,009
  9. 2015A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimationcited by 878
  10. 2016Unsupervised Monocular Depth Estimation with Left-Right Consistencycited by 819
  11. 2017Unsupervised Learning of Depth and Ego-Motion from Videocited by 778
  12. 2018MegaDepth: Learning Single-View Depth Prediction from Internet Photoscited by 731
38 more
  1. 2018Deep Ordinal Regression Network for Monocular Depth Estimationcited by 721
  2. 2020AdaBins: Depth Estimation using Adaptive Binscited by 596
  3. 2014Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecturecited by 483
  4. 2016Semantic Scene Completion from a Single Depth Imagecited by 468
  5. 2021Intriguing Properties of Vision Transformerscited by 446
  6. 20193D Packing for Self-Supervised Monocular Depth Estimationcited by 437
  7. 2016Deeper Depth Prediction with Fully Convolutional Residual Networkscited by 402
  8. 2019From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimationcited by 379
  9. 2016Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescuecited by 368
  10. 2019Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Videocited by 244
  11. 2020Consistent Video Depth Estimationcited by 220
  12. 2016DeMoN: Depth and Motion Network for Learning Monocular Stereocited by 200
  13. 2020Proxy Anchor Loss for Deep Metric Learningcited by 195
  14. 2021The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depthcited by 190
  15. 2020A2D2: Audi Autonomous Driving Datasetcited by 189
  16. 2018The ApolloScape Open Dataset for Autonomous Driving and its Applicationcited by 188
  17. 2020Robust Consistent Video Depth Estimationcited by 188
  18. 2016Single-Image Depth Perception in the Wildcited by 179
  19. 2015Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fieldscited by 169
  20. 2018Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstructioncited by 159
  21. 2018DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistencycited by 148
  22. 2019Self-Supervised Monocular Depth Hintscited by 127
  23. 2019Hierarchical Deep Stereo Matching on High-resolution Imagescited by 126
  24. 2021Transformer-Based Attention Networks for Continuous Pixel-Wise Predictioncited by 125
  25. 2020Self-supervised Monocular Trained Depth Estimation using Self-attention and Discrete Disparity Volumecited by 116
  26. 2017Semi-Supervised Deep Learning for Monocular Depth Map Predictioncited by 109
  27. 2021TransformerFusion: Monocular RGB Scene Reconstruction using Transformerscited by 107
  28. 2014Deep Convolutional Neural Fields for Depth Estimation from a Single Imagecited by 106
  29. 2021Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Mergingcited by 104
  30. 2018The TUM VI Benchmark for Evaluating Visual-Inertial Odometrycited by 94
  31. 2016Estimating Depth from Monocular Images as Classification Using Deep Fully Convolutional Residual Networkscited by 91
  32. 2020A Survey on Deep Learning Techniques for Stereo-based Depth Estimationcited by 90
  33. 2021Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Predictioncited by 88
  34. 2019Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Eracited by 87
  35. 2018Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometrycited by 85
  36. 2019How do neural networks see depth in single images?cited by 82
  37. 2020Guiding Monocular Depth Estimation Using Depth-Attention Volumecited by 82
  38. 2021Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimationcited by 80

50 most cited of 112 All 112 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 9; 2026: 5.

15 papers.

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  1. 2025UniFuture: A 4D Driving World Model for Future Generation and Perceptioncited by 21
  2. 2025Depth Anything at Any Conditioncited by 11
  3. 2025MonoTher-Depth: Enhancing Thermal Depth Estimation via Confidence-Aware Distillationcited by 5
  4. 2026StreamTTO: Efficient Online Test-Time Optimization for Video Depth Completioncited by 3
  5. 2025FlyAwareV2: A Multimodal Cross-Domain UAV Dataset for Urban Scene Understandingcited by 2
  6. 2025Endoscopic Depth Estimation Based on Deep Learning: A Surveycited by 1
  7. 2026LuMon: A Comprehensive Benchmark and Development Suite with Novel Datasets for Lunar Monocular Depth Estimationcited by 1
  8. 2026Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typographycited by 1
  9. 2026SS3D: End2End Self-Supervised 3D from Web Videoscited by 1
  10. 2024PhysDepth: Plug-and-Play Physical Refinement for Monocular Depth Estimation in Challenging Environmentscited by 0
  11. 2025Survey on Monocular Metric Depth Estimationcited by 0
  12. 2025MT-Depth: Multi-task Instance feature analysis for the Depth Completioncited by 0
3 more
  1. 2025Accuracy Does Not Guarantee Human-Likeness: Cross-Domain Human-Centered Benchmark in Monocular Depth Estimationcited by 0
  2. 2025Multi-scale Attention-Guided Intrinsic Decomposition and Rendering Pass Prediction for Facial Imagescited by 0
  3. 2026Learning Vision-Based Omnidirectional Navigation: A Teacher-Student Approach Using Monocular Depth Estimationcited by 0