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Scalable Image Retrieval by Sparse Product Quantization
2017
IEEE transactions on multimedia
Fast Approximate Nearest Neighbor (ANN) search technique for high-dimensional feature indexing and retrieval is the crux of large-scale image retrieval. A recent promising technique is Product Quantization, which attempts to index high-dimensional image features by decomposing the feature space into a Cartesian product of low dimensional subspaces and quantizing each of them separately. Despite the promising results reported, their quantization approach follows the typical hard assignment of
doi:10.1109/tmm.2016.2625260
fatcat:d4kllkspz5fvzdmruw6hsnzqra