度量学习中有一个问题:特征提取器产生的是feature map,然而距离度量函数需要的是一个对整张图的向量表示。所以需要找到一个方法将feature map转化成向量表示。理想状态下,这种转换既可以保留feature map的粒度信息和细节,又不会使模型过拟合。但想的太美了,现存的方法都不太彳亍。比如全局的average pooling,很粗暴的...
3.1 Feature Map Ridge Regression LetX_sdenote the set of support images with corresponding class labels in an n-way, k-way episode. 希望为单个输入query图像x_q预测一个类标签y_q,x_q的卷积特征提取器的输出是一个特征映射Q \in \mathbb{R}^{r \times d},空间分辨率为r,d为通道数,对于每个类...
Dynamic Memory Induction Networks for Few-Shot Text Classification acl 2020 论文地址: https://arxiv.org/pdf/2005.05727.pdf 简介:和Few-Shot Text Classification with Induction Network区别是编码模块使用bert-base,增加了pretrained的监督学习阶段。 网络结构: Pre-trained Encoder: 预训练+监督学习到类别向量,...
Dynamic Memory Induction Networks for Few-Shot Text Classification acl 2020 论文地址:https://arxiv.org/pdf/2005.05727.pdf简介:和Few-Shot Text Classification with Induction Network区别是编码模块使用bert-base,增加了pretrained的监督学习阶段。网络结构: Pre-trained Encoder:预训练+监督学习到类别向量,当做memo...
Few-Shot Classification with Feature Map Reconstruction Networks Davis Wertheimer*,Luming Tang*,Bharath Hariharan(* denotes equal contribution) CVPR 2021 (video) If you find our code or paper useful to your research work, please consider citing our work using the following bibtex: ...
关系网络的做法是将query set的特征表示和support set的特征表示concat一起,然后走mlp网络,最后softmax得到分类结果。当few-shot的情况,将同一类的feature_map进行相加。 网络结构: Few-Shot Text Classification with Induction Network 2018 论文地址: https://arxiv.org/pdf/1902.10482.pdf ...
Generating ClassificationWeights with GNN Denoising Autoencoders fo Few-Shot Learning (oral) motivation:利用去噪自编码器的思想,并考虑类间的关系,生成分类器的权重。由于小样本得到的分类器具有较大的噪声,所以可以采用去噪编码器对其精化。 方法: 利用所有的训练数据预训练一个特征提取器,并得到所有训练分类层的...
Few-shot classification with feature map reconstruction net- works. In Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition, pages 8012–8021, 2021. 2, 3, 5, 6, 7, 8 [43] Sanghyun Woo, Jongchan Park, Joon-Young Lee, and In So...
Few-shot classification (FSC) is one of the most concerned hot issues in recent years. The general setting consists of two phases: (1) Pre-train a feature extraction model (FEM) with base data (has large amounts of labeled samples). (2) Use the FEM to extract the features of novel ...
Few-Shot Classification With Feature Map Reconstruction Networks Davis Wertheimer, Luming Tang, Bharath Hariharan few-short问题中因为训练集不多,导致常见分类方法效果不理想,本文提出在特征空间中基于重构误差做图像分类 训练集每张图映射到特征空间,相同类别的组织在一起,$S_c$表示c类中用k个样本的特征。待分...