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Object Retrieval and Localization in Large Art Collections using Deep Multi-Style Feature Fusion and Iterative Voting
In the following, we introduce an algorithm that allows users to search for image regions containing specific motifs or objects and find similar regions in an extensive dataset, helping art historians to analyze large digitized art collections.
Multi-Scale Convolutions for Learning Context Aware Feature Representations
Finding semantic correspondences is a challenging problem.
Deep Semantic Feature Matching
We introduce a novel method for semantic matching with pre-trained CNN features which is based on convolutional feature pyramids and activation guided feature selection.
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