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
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)
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