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Found 3 papers, 3 papers with code
Unsupervised Semantic-based Aggregation of Deep Convolutional Features
In this paper, we propose a simple but effective semantic-based aggregation (SBA) method.
Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval
Without post-processing, Our IME layer achieves a boost in performance of state-of-the-art image retrieval methods with post-processing on most datasets, and needs less computational cost.
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Unsupervised Part-based Weighting Aggregation of Deep Convolutional Features for Image Retrieval
In this paper, we propose a simple but effective semantic part-based weighting aggregation (PWA) for image retrieval.
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