- 著者
- Yusuke Matsui Yusuke Uchida Hervé Jégou Shin'ichi Satoh
- 出版者
- The Institute of Image Information and Television Engineers
- 雑誌
- ITE Transactions on Media Technology and Applications (ISSN:21867364)
- 巻号頁・発行日
- vol.6, no.1, pp.2-10, 2018 (Released:2018-01-01)
- 参考文献数
- 53
- 被引用文献数
- 1 21
Product Quantization (PQ) search and its derivatives are popular and successful methods for large-scale approximated nearest neighbor search. In this paper, we review the fundamental algorithm of this class of algorithms and provide executable sample codes. We then provide a comprehensive survey of the recent PQ-based methods.
言及状況
外部データベース (DOI)
Twitter (8 users, 8 posts, 25 favorites)
Still struggling with some of the details of product quantizations but this seems like a really good survey... even has a numpy code block implementing PQ.
https://t.co/LOf9gfkS1r https://t.co/QSDIAtZVWk
https://t.co/igROSJWWqS “Fast search with GPUs begins to be studied, which might be one of the next promising directions for ANN research”
.@yu4u さん、PQ著者のJegouさん、佐藤先生とPQのサーベイ論文書いたので全員引用してください。本当にお願いします https://t.co/TI7oIrv9De