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Saliency-Guided Mutual Learning Network for Few-shot Fine-grained Visual Recognition. (arXiv:2305.07180v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Recognizing novel sub-categories with scarce samples is an essential and
challenging research topic in computer vision. Existing literature focus on
addressing this challenge through global-based or local-based representation
approaches. The former employs global feature representations for
recognization, which may lack fine-grained information. The latter captures
local relationships with complex structures, possibly leading to high model
complexity. To address the above challenges, this article proposes a novel
framework called SGML-Net for few-shot fine-grained visual recognition.
SGML-Net incorporates auxiliary information via saliency …
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