iSEAu aims to significantly advance the state-of-the-art of underwater scene sensing by bridging the gap in the use of data-driven methods in underwater perception, and by combining the respective advantages of SPCs, multispectral and conventional cameras. Investing in intensive knowledge transfer, the goal is to bring together the fields of computer vision, machine learning and remote sensing for optimally addressing the underwater visual sensing challenges. iSEAu will provide novel data-driven methodologies and technological solutions to researchers, scientists and users for underwater sensing of unmatched fidelity. The general objective of iSEAu is to introduce novel intelligent underwater scene sensing and analysis methods building on state-of-the-art (SoA) technologies and research results like deep-learning, self-supervised and weakly-supervised learning, detailed underwater EM propagation models, and SPAD-based imaging to significantly enhance the visual properties of underwater images and allow the use of SoA computer vision scene reconstruction and understanding methods to the underwater domain.
Funded by the EU Commission under the MSCA-IF H2020 Programme, Grant number: 101030367.