Siamese Network-based Framework for Open-set Domain Generalization | |
Geng Liu1,2 | |
2023-04 | |
会议名称 | International Conference on Frontiers of Artificial Intelligence and Machine Learning 2023 |
会议日期 | 2023-5 |
会议地点 | 北京 |
会议录编者/会议主办者 | 重庆大学 |
摘要 | Deep learning has made great progress in many fields, such as computer vision and natural language processing. But the performance of traditional deep learning models will be seriously degraded when facing the domain shift, which means that the distribution of test data and training data is significantly different. A large number of Domain Generalization (DG) methods have been proposed to enhance the generalizability of models. However, traditional DG methods are based on the assumption that the category space of training data and test data is consistent, which is always untenable in practice. Therefore, this paper further studies the open-set domain generalization problem when the category spaces of training data and test data are inconsistent. This paper proposes an open-set domain generalization framework based on the Siamese network, which generates images in the unknown categories through patch-shuffling, and treats generated images as negative samples to negatively supervise models. Thus models are forced to learn the critical feature representations, the over-fitting of models reduces, and then the performance of models on open-set domain generalization tasks is enhanced. The experimental results show that the proposed framework achieves state-of-the-art on the two open-set domain generalization benchmarks. |
关键词 | Domain generalization Image recognition Open-set recognition Siamese network |
学科门类 | 工学::计算机科学与技术(可授工学、理学学位) |
收录类别 | EI |
语种 | 英语 |
是否为代表性论文 | 否 |
七大方向——子方向分类 | 类脑模型与计算 |
国重实验室规划方向分类 | 脑启发多模态智能模型与算法 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/52318 |
专题 | 模式识别实验室 |
作者单位 | 1.University of Chinese Academy of Sciences 2.Institute of Automation, Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Geng Liu. Siamese Network-based Framework for Open-set Domain Generalization[C]//重庆大学,2023. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
IM020.docx(181KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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