AI RESEARCH
HFP-SAM: Hierarchical Frequency Prompted SAM for Efficient Marine Animal Segmentation
arXiv CS.CV
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ArXi:2603.12708v1 Announce Type: new Marine Animal Segmentation (MAS) aims at identifying and segmenting marine animals from complex marine environments. Most of previous deep learning-based MAS methods struggle with the long-distance modeling issue. Recently, Segment Anything Model (SAM) has gained popularity in general image segmentation. However, it lacks of perceiving fine-grained details and frequency information. To this end, we propose a novel learning framework, named Hierarchical Frequency Prompted SAM (HFP-SAM) for high-performance