mlsanityData to 14 Oct 2026

The Marine Debris Forward-Looking Sonar Datasets

arXiv 2503.22880 ↗First posted 28 Mar 2025cs.CV cs.LGcited by 4

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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

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

13 of 20 references.

References · 13

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  9. 2021The Marine Debris Dataset for Forward-Looking Sonar Semantic Segmentationcited by 22
  10. 2022Self-supervised Learning for Sonar Image Classificationcited by 12
  11. 2019Deep Neural Networks for Marine Debris Detection in Sonar Imagescited by 6
  12. 2017Improving Sonar Image Patch Matching via Deep Learningcited by 5
1 more
  1. 2021Pre-trained Models for Sonar Imagescited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026uScenes: A Multimodal RGB and 3D Sonar Dataset for Underwater Robot Perceptioncited by 2
  2. 2026MambaDSF: Multi-Scale SSM with Dilated Feature Fusion for Sonar Small Target Detectioncited by 0
  3. 2026Spiking Neural Networks for Energy-Efficient Object Detection in Forward-Looking Sonar Imagerycited by 0
  4. 2026Quantum-Gated LiteSSD: A Parameter-Efficient Lightweight Hybrid Quantum-Classical Framework for Forward-Looking Sonar Object Detectioncited by 0