A deep one-shot network for query-based logo retrieval

作者：

Highlights：

• A scalable solution is proposed for the logo detection problem by redesigning the traditional problem setting.

• It is based on one-shot learning framework.

• Multiscale conditioning network is employed to learn the similarity between the logos at multiple scales and resolutions.

• The method has been tested on FlickrsLogos and TopLogos datasets.

摘要

•A scalable solution is proposed for the logo detection problem by redesigning the traditional problem setting.•It is based on one-shot learning framework.•Multiscale conditioning network is employed to learn the similarity between the logos at multiple scales and resolutions.•The method has been tested on FlickrsLogos and TopLogos datasets.

论文关键词：Logo retrieval,One-shot learning,Multi-scale conditioning,Similarity matching,Query retrieval

论文评审过程：Received 12 February 2019, Revised 1 July 2019, Accepted 10 July 2019, Available online 11 July 2019, Version of Record 15 July 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.106965