In this project we investigated the indexing strategies for billion-scale datasets of deep descriptors, extracted from the last layers of convolutional neural networks. We have introduced two indexing structures: the Non-Orthogonal Inverted Multi-Index (NO-IMI) and the Generalized Non-Orthogonal Inverted Multi-Index. These structures continue the idea of the standard inverted multi-index but do not decompose the search space into orthogonal subspaces. We have demonstrated the success of the (G)NO-IMI on a new billion-scale dataset of deep descriptors (DEEP1B).
Paper: Artem Babenko and Victor Lempitsky, Efficient Indexing of Billion-Scale datasets of deep descriptors, CVPR 2016
The dataset contains: