Robust learning from noisy web data for fine-Grained recognition

作者：

Highlights：

• Mitigate the harmful effects of label noise and capture discriminative feature representations simultaneously

• Decouple the joint optimization to promote the generalization performance

• Refurbish training procedure with accumulated predictions and consistency

• Achieves state-of-the-art performance for the web-supervised fine-grained recognition task

摘要

•Mitigate the harmful effects of label noise and capture discriminative feature representations simultaneously•Decouple the joint optimization to promote the generalization performance•Refurbish training procedure with accumulated predictions and consistency•Achieves state-of-the-art performance for the web-supervised fine-grained recognition task

论文关键词：Fine-grained,Web-supervised,Noisy web data,Robust learning

论文评审过程：Received 9 August 2021, Revised 24 August 2022, Accepted 20 September 2022, Available online 23 September 2022, Version of Record 7 October 2022.

论文官网地址：https://doi.org/10.1016/j.patcog.2022.109063