Few-shot object detection via baby learning

作者：

Highlights：

• Introduce Baby Learning mechanism into few-shot object detection.

• Use multi-receptive fields to capture the novel variance object appearance in FSOD.

• Propose FORD + BL method to achieve superior results over the baseline.

• Flexibly apply Baby Learning mechanism to other FSOD methods.

摘要

•Introduce Baby Learning mechanism into few-shot object detection.•Use multi-receptive fields to capture the novel variance object appearance in FSOD.•Propose FORD + BL method to achieve superior results over the baseline.•Flexibly apply Baby Learning mechanism to other FSOD methods.

论文关键词：Few-shot object detection,Few-shot learning,Baby learning

论文评审过程：Received 8 November 2021, Revised 24 January 2022, Accepted 26 January 2022, Available online 1 February 2022, Version of Record 19 February 2022.

论文官网地址：https://doi.org/10.1016/j.imavis.2022.104398