AI RESEARCH
AIM 2025 Rip Current Segmentation (RipSeg) Challenge Report
arXiv CS.CV
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ArXi:2508.13401v3 Announce Type: replace This report presents an overview of the AIM 2025 RipSeg Challenge, a competition designed to advance techniques for automatic rip current segmentation in still images. Rip currents are dangerous, fast-moving flows that pose a major risk to beach safety worldwide, making accurate visual detection an important and underexplored research task. The challenge builds on RipVIS, the largest available rip current dataset, and focuses on single-class instance segmentation, where precise delineation is critical to fully capture the extent of rip currents.