Learn from each other to Classify better: Cross-layer mutual attention learning for fine-grained visual classification

Dichao Liu, Longjiao Zhao, Yu Wang, Jien Kato

Abstract: Highlights•A multi-step framework for improving the accuracy of fine-grained image recognition.•A design for different layers to learn from each other to boost overall performance.•Extensive experiments demonstrate and prove the effectiveness of the proposed idea.•The proposed method reports state-of-the-art results on three challenging datasets.