ANN代码说明文件

Last edit: lzwang, 2020/12/30

AQ

• Python源代码：https://github.com/arbabenko/Quantizations

• 相关论文：Babenko A, Lempitsky V. Additive quantization for extreme vector compression[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2014: 931-938.

BOPQ

• Matlab源代码：https://github.com/yutao1008/BOPQ

• 相关论文：Yu L, Huang Z, Shen F, et al. Bilinear optimized product quantization for scalable visual content analysis[J]. IEEE Transactions on Image Processing, 2017, 26(10): 5057-5069.

C-Kmeans

• Matlab源代码：https://github.com/norouzi/ckmeans

• 相关论文：Norouzi M, Fleet D J. Cartesian k-means[C]//Proceedings of the IEEE Conference on computer Vision and Pattern Recognition. 2013: 3017-3024.

OPQ

• Matlab源代码：http://kaiminghe.com/cvpr13/matlab_OPQ_release_v1.1.rar

• Python源代码：https://github.com/matsui528/nanopq

• 相关论文：

  1. Ge T, He K, Ke Q, et al. Optimized product quantization for approximate nearest neighbor search[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2013: 2946-2953.

  2. Ge T, He K, Ke Q, et al. Optimized product quantization[J]. IEEE transactions on pattern analysis and machine intelligence, 2013, 36(4): 744-755.

CQ

• CPP源代码：https://github.com/hellozting/CompositeQuantization

• 相关论文：

  1. Zhang T, Du C, Wang J. Composite Quantization for Approximate Nearest Neighbor Search[C]//ICML. 2014, 2: 3.

  2. [Wang J, Zhang T. Composite quantization[J]. IEEE transactions on pattern analysis and machine intelligence, 2018, 41(6): 1308-1322.](Composite quantization)

  3. Zhang T, Qi G J, Tang J, et al. Sparse composite quantization[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015: 4548-4556.

PQ _IVFADC

• CPP源代码：https://github.com/YangZhongy/PQ_IVFADC

• Matlab源代码：https://github.com/una-dinosauria/Product-Quantization-for-Approximate-Nearest-Neighbor-Search

• 相关论文：Jegou H, Douze M, Schmid C. Product quantization for nearest neighbor search[J]. IEEE transactions on pattern analysis and machine intelligence, 2010, 33(1): 117-128.

LOPQ

• Fast-lopq CPP源代码：https://github.com/dmllr/fast-lopq

• Yahoo-lopq源代码：https://github.com/yahoo/lopq

• 相关论文：Kalantidis Y, Avrithis Y. Locally optimized product quantization for approximate nearest neighbor search[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2014: 2321-2328.

LSQ

• Julia源代码：https://github.com/una-dinosauria/local-search-quantization

• Python源代码：https://github.com/xiaosu-zhu/LSQ-python

• 相关论文：Martinez J, Clement J, Hoos H H, et al. Revisiting additive quantization[C]//European Conference on Computer Vision. Springer, Cham, 2016: 137-153.

QPQ

• Matlab源代码：https://github.com/AnshanTJU/QuarterPointPQ

• 相关论文：An S, Huang Z, Bai S, et al. Quarter-Point Product Quantization for approximate nearest neighbor search[J]. Pattern Recognition Letters, 2019, 125: 187-194.

The Yael Library

• 简介：Yael is a library implementing computationally intensive functions used in large scale image retrieval, such as neighbor search, clustering and inverted files. The library offers interfaces for C, Python and Matlab.

• 相关链接：http://yael.gforge.inria.fr