mlsanityData to 14 Oct 2026

WS-SfMLearner: Self-supervised Monocular Depth and Ego-motion Estimation on Surgical Videos with Unknown Camera Parameters

arXiv 2308.11776 ↗First posted 22 Aug 2023cs.CV cs.AI eess.IVcited by 9

Not on the map. Why?

Abstract (arXiv)

Depth estimation in surgical video plays a crucial role in many image-guided surgery procedures. However, it is difficult and time consuming to create depth map ground truth datasets in surgical videos due in part to inconsistent brightness and noise in the surgical scene. Therefore, building an accurate and robust self-supervised depth and camera ego-motion estimation system is gaining more attention from the computer vision community. Although several self-supervision methods alleviate the need for ground truth depth maps and poses, they still need known camera intrinsic parameters, which are often missing or not recorded. Moreover, the camera intrinsic prediction methods in existing works depend heavily on the quality of datasets. In this work, we aimed to build a self-supervised depth and ego-motion estimation system which can predict not only accurate depth maps and camera pose, but also camera intrinsic parameters. We proposed a cost-volume-based supervision manner to give the system auxiliary supervision for camera parameters prediction. The experimental results showed that the proposed method improved the accuracy of estimated camera parameters, ego-motion, and depth estimation.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 31 of its 40 references that are in the map. First posted on arXiv 22 Aug 2023.

Builds on

31 of 40 references.

References · 31

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2017Unsupervised Learning of Depth and Ego-Motion from Videocited by 782
  4. 2018Deep Ordinal Regression Network for Monocular Depth Estimationcited by 723
  5. 2016Semantic Scene Completion from a Single Depth Imagecited by 472
  6. 2019Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Videocited by 244
  7. 2021The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depthcited by 190
  8. 2019Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Camerascited by 170
  9. 20192017 Robotic Instrument Segmentation Challengecited by 168
  10. 2020Feature-metric Loss for Self-supervised Learning of Depth and Egomotioncited by 140
  11. 2020Self-supervised Monocular Trained Depth Estimation using Self-attention and Discrete Disparity Volumecited by 116
  12. 2020HR-Depth: High Resolution Self-Supervised Monocular Depth Estimationcited by 115
19 more
  1. 2021Stereo Correspondence and Reconstruction of Endoscopic Data Challengecited by 103
  2. 2016Estimating Depth from Monocular Images as Classification Using Deep Fully Convolutional Residual Networkscited by 91
  3. 2021Self-Supervised Monocular Depth and Ego-Motion Estimation in Endoscopy: Appearance Flow to the Rescuecited by 72
  4. 2017Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimationcited by 70
  5. 2021Unsupervised Scale-consistent Depth Learning from Videocited by 69
  6. 2020DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learningcited by 60
  7. 2018LEGO: Learning Edge with Geometry all at Once by Watching Videoscited by 47
  8. 2023CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objectscited by 43
  9. 2020DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentationcited by 28
  10. 2022Min-Max Similarity: A Contrastive Semi-Supervised Deep Learning Network for Surgical Tools Segmentationcited by 28
  11. 2018Learning from a tiny dataset of manual annotations: a teacher/student approach for surgical phase recognitioncited by 21
  12. 2021Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Imagescited by 21
  13. 2022Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera Intrinsicscited by 19
  14. 2018Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robotscited by 14
  15. 2021CFPNet: Channel-wise Feature Pyramid for Real-Time Semantic Segmentationcited by 14
  16. 2023Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025cited by 12
  17. 2023False Negative/Positive Control for SAM on Noisy Medical Imagescited by 12
  18. 2021CamLessMonoDepth: Monocular Depth Estimation with Unknown Camera Parameterscited by 8
  19. 2022Self-Supervised Surgical Instrument 3D Reconstruction from a Single Camera Imagecited by 6

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 4; 2026: 1.

9 papers.

  1. 2024Transferring Relative Monocular Depth to Surgical Vision with Temporal Consistencycited by 13
  2. 2024NeuroBOLT: Resting-state EEG-to-fMRI Synthesis with Multi-dimensional Feature Mappingcited by 11
  3. 2025Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Reviewcited by 8
  4. 2024Surgical Depth Anything: Depth Estimation for Surgical Scenes using Foundation Modelscited by 5
  5. 2025SHADeS: Self-supervised Monocular Depth Estimation Through Non-Lambertian Image Decompositioncited by 3
  6. 2025ColonCrafter: A Depth Estimation Model for Colonoscopy Videos Using Diffusion Priorscited by 3
  7. 2025Learning to Efficiently Adapt Foundation Models for Self-Supervised Endoscopic 3D Scene Reconstruction from Any Camerascited by 1
  8. 2024DaRePlane: Direction-aware Representations for Dynamic Scene Reconstructioncited by 0
  9. 2026Confidence-aware Monocular Depth Estimation for Minimally Invasive Surgerycited by 0