English

OceanSAR-2: A Universal Feature Extractor for SAR Ocean Observation

Machine Learning 2026-01-13 v1 Artificial Intelligence Computer Vision and Pattern Recognition

Abstract

We present OceanSAR-2, the second generation of our foundation model for SAR-based ocean observation. Building on our earlier release, which pioneered self-supervised learning on Sentinel-1 Wave Mode data, OceanSAR-2 relies on improved SSL training and dynamic data curation strategies, which enhances performance while reducing training cost. OceanSAR-2 demonstrates strong transfer performance across downstream tasks, including geophysical pattern classification, ocean surface wind vector and significant wave height estimation, and iceberg detection. We release standardized benchmark datasets, providing a foundation for systematic evaluation and advancement of SAR models for ocean applications.

Cite

@article{arxiv.2601.07392,
  title  = {OceanSAR-2: A Universal Feature Extractor for SAR Ocean Observation},
  author = {Alexandre Tuel and Thomas Kerdreux and Quentin Febvre and Alexis Mouche and Antoine Grouazel and Jean-Renaud Miadana and Antoine Audras and Chen Wang and Bertrand Chapron},
  journal= {arXiv preprint arXiv:2601.07392},
  year   = {2026}
}

Comments

accepted at EUSAR 2026

R2 v1 2026-07-01T09:00:29.008Z