FGVC---细粒度图像分类文章收集

网文收集

综述型

论文笔记 | 基于深度学习的细粒度物体分类综述（A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation）
https://blog.csdn.net/u014593748/article/details/79964507

细粒度图像分类–CVPR2017 & ICCV2017论文总结
https://blog.csdn.net/liuxiao214/article/details/80945870

见微知著：细粒度图像分析进展（包括细露度图像分析和细粒度图像检索）
https://blog.csdn.net/heyc861221/article/details/80128952

值得借鉴的思想：目标检测中—基于弱监督的目标定位
Weakly Supervised Object Localization

具体方法

论文阅读笔记 | (ECCV 2018) Learning to Navigate for Fine-grained Classification
https://blog.csdn.net/qq_16525279/article/details/82595285

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

细粒度分类 | Bilinear model 以及相关的变形
https://blog.csdn.net/u012426298/article/details/81843405

ICCV2017—MACNN-Learning Multi-Attention Convolutional Neural Network for Fine-Grained Image Recognition
https://blog.csdn.net/ellin_young/article/details/80282081

ECCV2018 | 细粒度分类：多注意力多类别约束 Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition
https://blog.csdn.net/HongYuSuiXinLang/article/details/82854254

ECCV2018 Pairwise Confusion for Fine-Grained Visual Classification

CVPR2017 ORAL 基于递归注意力模型的卷积神经网络：让精细化物体分类成为现实 （RACNN）
https://www.msra.cn/zh-cn/news/features/ra-cnn-20170727
学界 | 微软亚洲研究院CVPR 2017 Oral论文：逐层集中Attention的卷积模型（RACNN）
https://cloud.tencent.com/developer/article/1119116
RA-CNN算法笔记
https://blog.csdn.net/u014380165/article/details/79244617
RACNN源码：https://github.com/jeong-tae/RACNN-pytorch

CVPR2018 | 细粒度分类 : Learning a Discriminative Filter Bank within a CNN（DFL-CNN） 及tensorflow实现
https://blog.csdn.net/HongYuSuiXinLang/article/details/82818541

论文笔记：Two-level attention model for fine-grained Image classification
原文：The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification
https://blog.csdn.net/baidu_17806763/article/details/70209567

细粒度图像识别Object-Part Attention Driven Discriminative Localization for Fine-grained Image Classification
https://blog.csdn.net/Cyiano/article/details/72081855?utm_source=blogkpcl8

论文阅读(1)–Fine-grained Image Classification by Exploring Bipartite-Graph Labels
https://blog.csdn.net/lc013/article/details/51895852

学界 |「分段映射」帮助利用少量样本习得新类别细粒度分类器
https://cloud.tencent.com/developer/article/1146905

全卷积注意网络的细粒度识别
https://cloud.tencent.com/developer/article/1099833

ACM MM | 中山大学等提出HSE：基于层次语义嵌入模型的精细化物体分类
https://cloud.tencent.com/developer/article/1345256

学界 | 精细识别现实世界图像：李飞飞团队提出半监督适应性模型
Fine-grained Recognition in the Wild: A Multi-Task Domain Adaptation Approach
https://cloud.tencent.com/developer/article/1119498

细粒度图像识别文章 Picking Deep Filter Responses for Fine-grained Image Recognition 阅读笔记
https://blog.csdn.net/cyiano/article/details/71629754

nips2018—Maximum Entropy Fine-Grained Classification

2020—DAF-NET: a saliency based weakly supervised method of dual attention fusion for fine-grained image classification

2020-Learning Cascade Attention for fine-grained image classification（代码开源）
2020-Spatial-Scale Aligned Network for Fine-Grained Recognition
2020-WSDM-Ultra Fine-Grained Image Semantic Embedding（基于graph，做正则)

源代码

• 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%）

• Pairwise Confusion for Fine-Grained Visual Classification
  https://github.com/abhimanyudubey/confusion

• RACNN源码：https://github.com/jeong-tae/RACNN-pytorch

• [NIPS 2018 论文笔记] Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning
  论文地址：http://papers.nips.cc/paper/7839-stacked-semantics-guided-attention-model-for-fine-grained-zero-shot-learning.pdf
  代码地址：https://github.com/ylytju/sga

• 2020–Learning Cascade Attention for fine-grained image classification
  源代码