Deep triplet residual quantization

作者：

Highlights：

• Offline training achieves promising results compared with online training.

• Local information help to improve the triplet numbers and quality.

• Optimize norm and angle separately provide flexible learning objectives.

摘要

•Offline training achieves promising results compared with online training.•Local information help to improve the triplet numbers and quality.•Optimize norm and angle separately provide flexible learning objectives.

论文关键词：Deep learning,Quantization,Triplet loss,Approximate nearest neighbor search

论文评审过程：Received 30 September 2020, Revised 21 April 2021, Accepted 21 June 2021, Available online 24 June 2021, Version of Record 9 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115467