mlsanityData to 7 Oct 2026

DepthTransfer: Depth Extraction from Video Using Non-parametric Sampling

arXiv 2001.00987 ↗First posted 24 Dec 2019cs.CVcited by 60

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Abstract (arXiv)

We describe a technique that automatically generates plausible depth maps from videos using non-parametric depth sampling. We demonstrate our technique in cases where past methods fail (non-translating cameras and dynamic scenes). Our technique is applicable to single images as well as videos. For videos, we use local motion cues to improve the inferred depth maps, while optical flow is used to ensure temporal depth consistency. For training and evaluation, we use a Kinect-based system to collect a large dataset containing stereoscopic videos with known depths. We show that our depth estimation technique outperforms the state-of-the-art on benchmark databases. Our technique can be used to automatically convert a monoscopic video into stereo for 3D visualization, and we demonstrate this through a variety of visually pleasing results for indoor and outdoor scenes, including results from the feature film Charade.

Key facts. Cited by 60 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Dec 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 24; 2022: 14; 2023: 11; 2024: 4; 2025: 3; 2026: 4.

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  1. 2021The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depthcited by 190
  2. 2022P3Depth: Monocular Depth Estimation with a Piecewise Planarity Priorcited by 106
  3. 2021Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimationcited by 63
  4. 2021360MonoDepth: High-Resolution 360deg Monocular Depth Estimationcited by 60
  5. 2023NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detectioncited by 51
  6. 2022SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenescited by 50
  7. 2021Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Predictioncited by 48
  8. 2024ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth Estimationcited by 45
  9. 2021Adaptive Surface Normal Constraint for Depth Estimationcited by 43
  10. 2021MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environmentscited by 38
  11. 2021Single Image Depth Estimation: An Overviewcited by 35
  12. 2023HairStep: Transfer Synthetic to Real Using Strand and Depth Maps for Single-View 3D Hair Modelingcited by 35
38 more
  1. 2021SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular imagescited by 33
  2. 2022Less is More: Consistent Video Depth Estimation with Masked Frames Modelingcited by 30
  3. 2022Sparsity Agnostic Depth Completioncited by 27
  4. 2023PanelNet: Understanding 360 Indoor Environment via Panel Representationcited by 19
  5. 2021Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimationcited by 16
  6. 2024Deep Learning-based Depth Estimation Methods from Monocular Image and Videos: A Comprehensive Surveycited by 15
  7. 2023Deep Learning for Visual Localization and Mapping: A Surveycited by 14
  8. 2021Real-time Monocular Depth Estimation with Sparse Supervision on Mobilecited by 12
  9. 2021X-Distill: Improving Self-Supervised Monocular Depth via Cross-Task Distillationcited by 12
  10. 2021Contrastive Feature Loss for Image Predictioncited by 12
  11. 2021GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional Networkcited by 12
  12. 2022MonoIndoor++:Towards Better Practice of Self-Supervised Monocular Depth Estimation for Indoor Environmentscited by 12
  13. 2024Ensuring UAV Safety: A Vision-only and Real-time Framework for Collision Avoidance Through Object Detection, Tracking, and Distance Estimationcited by 11
  14. 2022SfM-TTR: Using Structure from Motion for Test-Time Refinement of Single-View Depth Networkscited by 10
  15. 2023SwinDepth: Unsupervised Depth Estimation using Monocular Sequences via Swin Transformer and Densely Cascaded Networkcited by 10
  16. 2021EdgeConv with Attention Module for Monocular Depth Estimationcited by 9
  17. 2021Boundary-induced and scene-aggregated network for monocular depth predictioncited by 8
  18. 2023Joint Self-supervised Depth and Optical Flow Estimation towards Dynamic Objectscited by 8
  19. 2021Self-supervised Depth Estimation Leveraging Global Perception and Geometric Smoothness Using On-board Videoscited by 7
  20. 2023Deeper into Self-Supervised Monocular Indoor Depth Estimationcited by 7
  21. 2024Self-supervised Monocular Depth Estimation on Water Scenes via Specular Reflection Priorcited by 7
  22. 2022Pyramid Frequency Network with Spatial Attention Residual Refinement Module for Monocular Depth Estimationcited by 6
  23. 20223D-PL: Domain Adaptive Depth Estimation with 3D-aware Pseudo-Labelingcited by 6
  24. 2023NVDS+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimationcited by 6
  25. 2021Unsupervised Monocular Depth Perception: Focusing on Moving Objectscited by 4
  26. 2022How Far Can I Go ? : A Self-Supervised Approach for Deterministic Video Depth Forecastingcited by 3
  27. 2021ADAADepth: Adapting Data Augmentation and Attention for Self-Supervised Monocular Depth Estimationcited by 2
  28. 2021Dilated Fully Convolutional Neural Network for Depth Estimation from a Single Imagecited by 2
  29. 2021Adaptive Illumination based Depth Sensing using Deep Superpixel and Soft Sampling Approximationcited by 2
  30. 2023ADU-Depth: Attention-based Distillation with Uncertainty Modeling for Depth Estimationcited by 2
  31. 2026DAGE: Dual-Stream Architecture for Efficient and Fine-Grained Geometry Estimationcited by 2
  32. 2021Self-Supervised Learning of Depth and Ego-Motion from Video by Alternative Training and Geometric Constraints from 3D to 2Dcited by 1
  33. 2022Self-Supervised Depth Estimation with Isometric-Self-Sample-Based Learningcited by 1
  34. 2022Rethinking Skip Connections in Encoder-decoder Networks for Monocular Depth Estimationcited by 1
  35. 2022Improving Pixel-Level Contrastive Learning by Leveraging Exogenous Depth Informationcited by 1
  36. 2021A Weakly-Supervised Depth Estimation Network Using Attention Mechanismcited by 0
  37. 2021Sparse Depth Completion with Semantic Mesh Deformation Optimizationcited by 0
  38. 2021Improving Depth Estimation using Location Informationcited by 0

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