PQTable: Fast Exact Asymmetric Distance Neighbor Search for Product Quantization Using Hash Tables

PQTable: Fast Exact Asymmetric Distance Neighbor Search for Product Quantization Using Hash Tables
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DOI:
10.1109/iccv.2015.225
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发表时间:
2015-12
期刊:
2015 IEEE International Conference on Computer Vision (ICCV)
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通讯作者:
Yusuke Matsui;T. Yamasaki;K. Aizawa
Yusuke Matsui;T. Yamasaki;K. Aizawa
中科院分区:
其他
文献类型:
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作者:
Yusuke Matsui;T. Yamasaki;K. Aizawa

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我们提出了产品量化表(PQTable),一个产品量化为基础的哈希表,是快速的,既不需要参数调整,也不需要训练步骤。PQTable产生的结果与线性PQ搜索完全相同,并且在SIFT 1B数据上测试时快102到105倍。此外,虽然通过以前的基于反向索引的方法可以实现最先进的性能,但这些方法确实需要手动设计的参数设置和大量训练,而我们的方法不需要它们。因此,PQTable为现实世界的问题提供了一个实用和有用的解决方案。
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 102 to 105 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.