MATANet: A Multi-context Attention and Taxonomy-Aware Network for Fine-Grained Underwater Recognition of Marine Species 文章

arXiv:2601.03729v2 Announce Type: replace Abstract: Fine-grained recognition of marine organisms is important for ecological research, biodiversity monitoring, habitat conservation, and evidence-based policy-making. However, many existing approaches primarily rely on object- or ROI-centered representations. These limitations can reduce discriminative performance in challenging underwater scenes, where visually similar organisms often appear under diverse environmental conditions. To address these challenges, we propose MATANet (Multi-context Attention and Taxonomy-Aware Network), a framework for fine-grained taxonomic recognition of marine organisms. MATANet is motivated by expert taxonomic identification practices, in which both organism-level morphology and contextual cues are considered during recognition. The framework consists of two main components.