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Revisiting Local Descriptors via Frequent Pattern Mining for Fine-Grained Image Retrieval
2022
Entropy
Fine-grained image retrieval aims at searching relevant images among fine-grained classes given a query. The main difficulty of this task derives from the small interclass distinction and the large intraclass variance of fine-grained images, posing severe challenges to the methods that only resort to global or local features. In this paper, we propose a novel fine-grained image retrieval method, where global–local aware feature representation is learned. Specifically, the global feature is
doi:10.3390/e24020156
pmid:35205452
pmcid:PMC8871172
fatcat:skhn7z2khff67gjb7x4a6wbxne