Challenging deep image descriptors for retrieval in heterogeneous iconographic collections

no code implementations • 19 Sep 2019 • Dimitri Gominski, Martyna Poreba, Valérie Gouet-Brunet, Liming Chen

This article proposes to study the behavior of recent and efficient state-of-the-art deep-learning based image descriptors for content-based image retrieval, facing a panel of complex variations appearing in heterogeneous image datasets, in particular in cultural collections that may involve multi-source, multi-date and multi-view Permission to make digital

Content-Based Image Retrieval Retrieval