论文阅读笔记《Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders》
核心思想 本文提出一种基于变分自动编码器的广义零样本学习算法，通过结合图像特征信息和描述特征信息来构建包含重要的多模型信息的潜在特征，并借此实现对于未见过的（unseen）样本的分类。要想理解本文必须要先了解两个基础概念：广义零样本学习（Generalized zero-shot learning，GZSL）和变分自动编码器（Variational Autoencoders，VAE）。 零
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相关文章
- 1. [CVPR 2019 论文笔记] Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
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