mlsanityData to 14 Oct 2026

Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics

arXiv 1906.05717 ↗First posted 12 Jun 2019cs.CV cs.ROcited by 49

Not on the map. Why?

Abstract (arXiv)

We present an approach which takes advantage of both structure and semantics for unsupervised monocular learning of depth and ego-motion. More specifically, we model the motion of individual objects and learn their 3D motion vector jointly with depth and ego-motion. We obtain more accurate results, especially for challenging dynamic scenes not addressed by previous approaches. This is an extended version of Casser et al. [AAAI'19]. Code and models have been open sourced at https://sites.google.com/corp/view/struct2depth.

Key facts. Cited by 49 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Jun 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 12; 2022: 9; 2023: 12; 2024: 12; 2025: 0; 2026: 4.

49 papers.

Sort:

By area:

  1. 2021The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depthcited by 190
  2. 2022Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimationcited by 100
  3. 2022LocalBins: Improving Depth Estimation by Learning Local Distributionscited by 94
  4. 2021Unsupervised Scale-consistent Depth Learning from Videocited by 69
  5. 2021Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistencycited by 58
  6. 2022Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depthcited by 48
  7. 2021Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentationcited by 31
  8. 2024Cross-View Completion Models are Zero-shot Correspondence Estimatorscited by 30
  9. 2021Unsupervised Monocular Depth Estimation in Highly Complex Environmentscited by 28
  10. 2021SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Camerascited by 25
  11. 2021Attentive and Contrastive Learning for Joint Depth and Motion Field Estimationcited by 24
  12. 2023SQLdepth: Generalizable Self-Supervised Fine-Structured Monocular Depth Estimationcited by 21
37 more
  1. 2023CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentationcited by 18
  2. 2023DualRefine: Self-Supervised Depth and Pose Estimation Through Iterative Epipolar Sampling and Refinement Toward Equilibriumcited by 16
  3. 2023An End-to-end Food Portion Estimation Framework Based on Shape Reconstruction from Monocular Imagecited by 15
  4. 2024Deep Learning-based Depth Estimation Methods from Monocular Image and Videos: A Comprehensive Surveycited by 15
  5. 2023Self-Supervised Monocular Depth Estimation by Direction-aware Cumulative Convolution Networkcited by 14
  6. 2024SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera Imagescited by 13
  7. 2023Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedbackcited by 10
  8. 2022HandsOff: Labeled Dataset Generation With No Additional Human Annotationscited by 9
  9. 2024Embodiment: Self-Supervised Depth Estimation Based on Camera Modelscited by 9
  10. 2023Joint Depth Prediction and Semantic Segmentation with Multi-View SAMcited by 8
  11. 2024SPIdepth: Strengthened Pose Information for Self-supervised Monocular Depth Estimationcited by 8
  12. 2021LiDARTouch: Monocular metric depth estimation with a few-beam LiDARcited by 7
  13. 2022MonoDVPS: A Self-Supervised Monocular Depth Estimation Approach to Depth-aware Video Panoptic Segmentationcited by 7
  14. 2024Out of the Room: Generalizing Event-Based Dynamic Motion Segmentation for Complex Scenescited by 7
  15. 2024ProDepth: Boosting Self-Supervised Multi-Frame Monocular Depth with Probabilistic Fusioncited by 6
  16. 2021Unsupervised Joint Learning of Depth, Optical Flow, Ego-motion from Videocited by 5
  17. 2023Towards Better Data Exploitation in Self-Supervised Monocular Depth Estimationcited by 4
  18. 2024MAL: Motion-Aware Loss with Temporal and Distillation Hints for Self-Supervised Depth Estimationcited by 4
  19. 2024MambaDepth: Enhancing Long-range Dependency for Self-Supervised Fine-Structured Monocular Depth Estimationcited by 4
  20. 2023Camera Height Doesn't Change: Unsupervised Training for Metric Monocular Road-Scene Depth Estimationcited by 3
  21. 2023PPEA-Depth: Progressive Parameter-Efficient Adaptation for Self-Supervised Monocular Depth Estimationcited by 3
  22. 2021On the Coupling of Depth and Egomotion Networks for Self-Supervised Structure from Motioncited by 2
  23. 2022Multi-view Monocular Depth and Uncertainty Prediction with Deep SfM in Dynamic Environmentscited by 2
  24. 2023FLODCAST: Flow and Depth Forecasting via Multimodal Recurrent Architecturescited by 2
  25. 2024BaseBoostDepth: Exploiting Larger Baselines For Self-supervised Monocular Depth Estimationcited by 2
  26. 2024Geometric Constraints in Deep Learning Frameworks: A Surveycited by 1
  27. 2026Improved monocular depth prediction using distance transform over pre-semantic contours with self-supervised neural networkscited by 1
  28. 2026Scene-Centric Unsupervised Video Panoptic Segmentationcited by 1
  29. 2021A LiDAR Assisted Control Module with High Precision in Parking Scenarios for Autonomous Driving Vehiclecited by 0
  30. 2021Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videoscited by 0
  31. 2022Unsupervised Learning of Depth, Camera Pose and Optical Flow from Monocular Videocited by 0
  32. 2022Mapping the ocular surface from monocular videos with an application to dry eye disease gradingcited by 0
  33. 20223D Object Aided Self-Supervised Monocular Depth Estimationcited by 0
  34. 2023Unified Perception: Efficient Depth-Aware Video Panoptic Segmentation with Minimal Annotation Costscited by 0
  35. 2024Self-supervised Monocular Depth and Pose Estimation for Endoscopy with Latent Priorscited by 0
  36. 2026JEPADepth: Masked Predictive Representation Learning for Self-Supervised Monocular Depth Estimationcited by 0
  37. 2026XiDepth: a Lightweight and Efficient Network for Self-supervised Monocular Depth Estimationcited by 0