PQTable: Fast Exact Asymmetric Distance Neighbor Search for Product Quantization Using Hash Tables
Abstract
We propose the product quantization table (PQTable), a product quantization-based hash table that is fast and requires neither parameter tuning nor training steps. The PQTable produces exactly the same results as a linear PQ search, and is 10^2 to 10^5 times faster when tested on the SIFT1B data. In addition, although state-of-the-art performance can be achieved by previous inverted-indexing-based approaches, such methods do require manually designed parameter setting and much training, whereas our method is free from them. Therefore, PQTable offers a practical and useful solution for real-world problems.
Cite
Text
Matsui et al. "PQTable: Fast Exact Asymmetric Distance Neighbor Search for Product Quantization Using Hash Tables." International Conference on Computer Vision, 2015. doi:10.1109/ICCV.2015.225Markdown
[Matsui et al. "PQTable: Fast Exact Asymmetric Distance Neighbor Search for Product Quantization Using Hash Tables." International Conference on Computer Vision, 2015.](https://mlanthology.org/iccv/2015/matsui2015iccv-pqtable/) doi:10.1109/ICCV.2015.225BibTeX
@inproceedings{matsui2015iccv-pqtable,
title = {{PQTable: Fast Exact Asymmetric Distance Neighbor Search for Product Quantization Using Hash Tables}},
author = {Matsui, Yusuke and Yamasaki, Toshihiko and Aizawa, Kiyoharu},
booktitle = {International Conference on Computer Vision},
year = {2015},
doi = {10.1109/ICCV.2015.225},
url = {https://mlanthology.org/iccv/2015/matsui2015iccv-pqtable/}
}