# Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robots

arXiv: https://arxiv.org/abs/1803.01047 · HTML: https://mlsanity.com/paper/1803.01047/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Mar 2018.

## Built on by (most cited first, 14 of 14)

- [Self-Supervised Monocular Depth and Ego-Motion Estimation in Endoscopy: Appearance Flow to the Rescue](https://mlsanity.com/paper/2112.08122/) (2021)
- [SAGE: SLAM with Appearance and Geometry Prior for Endoscopy](https://mlsanity.com/paper/2202.09487/) (2022)
- [Bimodal Camera Pose Prediction for Endoscopy](https://mlsanity.com/paper/2204.04968/) (2022)
- [Advancing Dense Endoscopic Reconstruction with Gaussian Splatting-driven Surface Normal-aware Tracking and Mapping](https://mlsanity.com/paper/2501.19319/) (2025)
- [WS-SfMLearner: Self-supervised Monocular Depth and Ego-motion Estimation on Surgical Videos with Unknown Camera Parameters](https://mlsanity.com/paper/2308.11776/) (2023)
- [On the Uncertain Single-View Depths in Colonoscopies](https://mlsanity.com/paper/2112.08906/) (2021)
- [Depth estimation of endoscopy using sim-to-real transfer](https://mlsanity.com/paper/2112.13595/) (2021)
- [Task-guided Domain Gap Reduction for Monocular Depth Prediction in Endoscopy](https://mlsanity.com/paper/2310.01663/) (2023)
- [Learning-Based Depth and Pose Estimation for Monocular Endoscope with Loss Generalization](https://mlsanity.com/paper/2107.13263/) (2021)
- [A comprehensive survey on recent deep learning-based methods applied to surgical data](https://mlsanity.com/paper/2209.01435/) (2022)
- [Deep Neural Networks for Accurate Depth Estimation with Latent Space Features](https://mlsanity.com/paper/2502.11777/) (2025)
- [EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised Training](https://mlsanity.com/paper/2506.16017/) (2025)
- [EndoGMDE: Generalizable Monocular Depth Estimation with Mixture of Low-Rank Experts for Diverse Endoscopic Scenes](https://mlsanity.com/paper/2509.01206/) (2025)
- [Monocular Depth Estimation from a Single Image: Progress and Opportunities](https://mlsanity.com/paper/2609.01172/) (2026)

## Abstract (arXiv)

In the last decade, many medical companies and research groups have tried to convert passive capsule endoscopes as an emerging and minimally invasive diagnostic technology into actively steerable endoscopic capsule robots which will provide more intuitive disease detection, targeted drug delivery and biopsy-like operations in the gastrointestinal(GI) tract. In this study, we introduce a fully unsupervised, real-time odometry and depth learner for monocular endoscopic capsule robots. We establish the supervision by warping view sequences and assigning the re-projection minimization to the loss function, which we adopt in multi-view pose estimation and single-view depth estimation network. Detailed quantitative and qualitative analyses of the proposed framework performed on non-rigidly deformable ex-vivo porcine stomach datasets proves the effectiveness of the method in terms of motion estimation and depth recovery.