# The Marine Debris Forward-Looking Sonar Datasets

arXiv: https://arxiv.org/abs/2503.22880 · HTML: https://mlsanity.com/paper/2503.22880/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 20 references that are in the map.
- First posted on arXiv 28 Mar 2025.

## Builds on (most cited first, 13 of 13)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [ImageNet Large Scale Visual Recognition Challenge](https://mlsanity.com/paper/1409.0575/) (2014)
- [Densely Connected Convolutional Networks](https://mlsanity.com/paper/1608.06993/) (2016)
- [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://mlsanity.com/paper/1704.04861/) (2017)
- [SSD: Single Shot MultiBox Detector](https://mlsanity.com/paper/1512.02325/) (2015)
- [SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size](https://mlsanity.com/paper/1602.07360/) (2016)
- [The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale](https://mlsanity.com/paper/1811.00982/) (2018)
- [CNN Features off-the-shelf: an Astounding Baseline for Recognition](https://mlsanity.com/paper/1403.6382/) (2014)
- [The Marine Debris Dataset for Forward-Looking Sonar Semantic Segmentation](https://mlsanity.com/paper/2108.06800/) (2021)
- [Self-supervised Learning for Sonar Image Classification](https://mlsanity.com/paper/2204.09323/) (2022)
- [Deep Neural Networks for Marine Debris Detection in Sonar Images](https://mlsanity.com/paper/1905.05241/) (2019)
- [Improving Sonar Image Patch Matching via Deep Learning](https://mlsanity.com/paper/1709.02150/) (2017)
- [Pre-trained Models for Sonar Images](https://mlsanity.com/paper/2108.01111/) (2021)

## Built on by (most cited first, 4 of 4)

- [uScenes: A Multimodal RGB and 3D Sonar Dataset for Underwater Robot Perception](https://mlsanity.com/paper/2608.27795/) (2026)
- [MambaDSF: Multi-Scale SSM with Dilated Feature Fusion for Sonar Small Target Detection](https://mlsanity.com/paper/2605.24928/) (2026)
- [Spiking Neural Networks for Energy-Efficient Object Detection in Forward-Looking Sonar Imagery](https://mlsanity.com/paper/2608.22072/) (2026)
- [Quantum-Gated LiteSSD: A Parameter-Efficient Lightweight Hybrid Quantum-Classical Framework for Forward-Looking Sonar Object Detection](https://mlsanity.com/paper/2609.14025/) (2026)

## Abstract (arXiv)

Sonar sensing is fundamental for underwater robotics, but limited by capabilities of AI systems, which need large training datasets. Public data in sonar modalities is lacking. This paper presents the Marine Debris Forward-Looking Sonar datasets, with three different settings (watertank, turntable, flooded quarry) increasing dataset diversity and multiple computer vision tasks: object classification, object detection, semantic segmentation, patch matching, and unsupervised learning. We provide full dataset description, basic analysis and initial results for some tasks. We expect the research community will benefit from this dataset, which is publicly available at https://doi.org/10.5281/zenodo.15101686