AI RESEARCH
Modality-Agnostic Prompt Learning for Multi-Modal Camouflaged Object Detection
arXiv CS.CV
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ArXi:2604.12380v1 Announce Type: new Camouflaged Object Detection (COD) aims to segment objects that blend seamlessly into complex backgrounds, with growing interest in exploiting additional visual modalities to enhance robustness through complementary information. However, most existing approaches generally rely on modality-specific architectures or customized fusion strategies, which limit scalability and cross-modal generalization.