| 零样本学习综述 |
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| 引用本文： | 王泽深,杨云,向鸿鑫,柳青.零样本学习综述[J].计算机工程与应用,2021,57(19):1-17. |
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| 作者姓名： | 王泽深 杨云 向鸿鑫 柳青 |
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| 作者单位： | 1.云南大学 软件学院，昆明 650504
2.云南省数据科学与智能计算重点实验室，昆明 650504 |
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| 摘 要： | 尽管自深度学习发展以来，减少大量人工标记样本的需求使得零样本学习取得了不错的进展，以至于已经拥有比较完善的理论体系。但是对于零样本学习应用的研究寥寥无几，如何有效地对应用领域进行梳理是现阶段急需解决的问题。对零样本的理论体系进行介绍，通过一个例子引出零样本学习的定义，继而与广义零样本、监督学习比较，再而列举4个关键问题以及现有的解决方案，给出文本、图像、视频三方面常用的数据集；按照关键技术（属性、嵌入以及生成模型）出现时间顺序，对13个典型模型如何进行零样本学习展开描述，并对优点、缺点、创新点、挑选数据集以及表现进行总结；从词、图像、视频3个维度详细介绍了零样本学习在各个领域的应用；提出了零样本学习过程中出现的挑战并给出了对应的潜在研究方向。
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| 关 键 词： | 零样本学习 属性 嵌入空间 生成模型 |
Survey on Zero-Shot Learning |
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| WANG Zeshen,YANG Yun,XIANG Hongxin,LIU Qing.Survey on Zero-Shot Learning[J].Computer Engineering and Applications,2021,57(19):1-17. |
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| Authors: | WANG Zeshen YANG Yun XIANG Hongxin LIU Qing |
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| Affiliation: | 1.School of Software, Yunnan University, Kunming 650504, China
2.Yunnan Key Laboratory of Data Science and Intelligent Computing, Kunming 650504, China |
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| Abstract: | Although there have been well developed in zero-shot learning since the development of deep learning, in the aspect of the application, zero-shot learning did not have a good system to order it. This paper overviews theoretical systems of zero-shot learning, typical models, application systems, present challenges and future research directions. Firstly, it introduces the theoretical systems from definition of zero-shot learning, essential problems, and commonly used data sets. Secondly, some typical models of zero-shot learning are described in chronological order. Thirdly, it presents the application systems about of zero-shot learning from the three dimensions, such as words, images and videos. Finally, the paper analyzes the challenges and future research directions in zero-shot learning. |
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| Keywords: | zero-shot learning attribute embedding space general model |
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