ICCV2017 Dynamic Computational Time for Recurrent Attention Model (DT-RAM)

https://github.com/baidu-research/DT-RAM（Torch实现，ResNet的baseline很牛，CUB-200-2011数据集 84.5%，论文方法 86.0%）
http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w18/Li_Dynamic_Computational_Time_ICCV_2017_paper.pdf

ECCV2018 Learning to Navigate for Fine-grained Classification

https://github.com/yangze0930/NTS-Net（Pytorch实现，CUB-200-2011数据集 87.6%）
http://openaccess.thecvf.com/content_ECCV_2018/papers/Ze_Yang_Learning_to_Navigate_ECCV_2018_paper.pdf

CVPR 2018 Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition

https://github.com/songdejia/DFL-CNN（Pytorch第三方实现，值得借鉴，但无法复现原文）
https://arxiv.org/abs/1611.09932（CUB-200-2011数据集 87.4%）

ECCV 2018 Pairwise Confusion for Fine-Grained Visual Classification

http://openaccess.thecvf.com/content_ECCV_2018/papers/Abhimanyu_Dubey_Improving_Fine-Grained_Visual_ECCV_2018_paper.pdf

ECCV 2018 Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition

http://openaccess.thecvf.com/content_ECCV_2018/papers/Ming_Sun_Multi-Attention_Multi-Class_Constraint_ECCV_2018_paper.pdf

ECCV 2018 Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition

http://openaccess.thecvf.com/content_ECCV_2018/papers/Chaojian_Yu_Hierarchical_Bilinear_Pooling_ECCV_2018_paper.pdf

ECCV 2018 Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification

http://openaccess.thecvf.com/content_ECCV_2018/papers/Xing_Wei_Grassmann_Pooling_for_ECCV_2018_paper.pdf

 

参考：https://blog.csdn.net/wjbwjbwjbwjb/article/details/84728344

基于深度卷积特征的细粒度图像分类研究综述：https://zhuanlan.zhihu.com/p/24738319