# SubPipe: A Submarine Pipeline Inspection Dataset for Segmentation and Visual-inertial Localization

arXiv: https://arxiv.org/abs/2401.17907 · HTML: https://mlsanity.com/paper/2401.17907/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jan 2024.

## Built on by (most cited first, 7 of 7)

- [Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges](https://mlsanity.com/paper/2412.11840/) (2024)
- [BenthiCat: An opti-acoustic dataset for advancing benthic classification and habitat mapping](https://mlsanity.com/paper/2510.04876/) (2025)
- [ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling](https://mlsanity.com/paper/2503.17856/) (2025)
- [Sonar Image Datasets: A Comprehensive Survey of Resources, Challenges, and Applications](https://mlsanity.com/paper/2510.03353/) (2025)
- [USIM and U0: A Vision-Language-Action Dataset and Model for General Underwater Robots](https://mlsanity.com/paper/2510.07869/) (2025)
- [Attenuation-Aware Weighted Optical Flow with Medium Transmission Map for Learning-based Visual Odometry in Underwater terrain](https://mlsanity.com/paper/2407.13159/) (2024)
- [YOLO-Based Pipeline Monitoring in Challenging Visual Environments](https://mlsanity.com/paper/2507.02967/) (2025)

## Abstract (arXiv)

This paper presents SubPipe, an underwater dataset for SLAM, object detection, and image segmentation. SubPipe has been recorded using a glsLAUV, operated by OceanScan MST, and carrying a sensor suite including two cameras, a side-scan sonar, and an inertial navigation system, among other sensors. The AUV has been deployed in a pipeline inspection environment with a submarine pipe partially covered by sand. The AUV's pose ground truth is estimated from the navigation sensors. The side-scan sonar and RGB images include object detection and segmentation annotations, respectively. State-of-the-art segmentation, object detection, and SLAM methods are benchmarked on SubPipe to demonstrate the dataset's challenges and opportunities for leveraging computer vision algorithms. To the authors' knowledge, this is the first annotated underwater dataset providing a real pipeline inspection scenario. The dataset and experiments are publicly available online at https://github.com/remaro-network/SubPipe-dataset