Introspective GAN: Learning to grow a GAN for incremental generation and classification
文献类型：期刊论文
| 作者 | He, Chen1; Wang, Ruiping1; Shan, Shiguang1; Chen, Xilin1 |
| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 2024-07-01 |
| 卷号 | 151页码:12 |
| 关键词 | Incremental learning Catastrophic forgetting Generative Adversarial Networks |
| ISSN号 | 0031-3203 |
| DOI | 10.1016/j.patcog.2024.110383 |
| 英文摘要 | Lifelong learning, the ability to continually learn new concepts throughout our life, is a hallmark of human intelligence. Generally, humans learn a new concept by knowing what it looks like and what makes it different from the others , which are correlated. Those two ways can be characterized by generation and classification in machine learning respectively. In this paper, we carefully design a dynamically growing GAN called Introspective GAN (IntroGAN) that can perform incremental generation and classification simultaneously with the guidance of prototypes, inspired by their roles of efficient information organization in human visual learning and excellent performance in other fields like zero-shot/few-shot/incremental learning. Specifically, we incorporate prototype-based classification which is robust to feature change in incremental learning and GAN as a generative memory to alleviate forgetting into a unified end -to -end framework. A comprehensive benchmark on the joint incremental generation and classification task is proposed and our method demonstrates promising results. Additionally, we conduct comprehensive analyses over the properties of IntroGAN and verify that generation and classification can be mutually beneficial in incremental scenarios, which is an inspiring area to be further exploited. The code is available at https://github.com/TonyPod/ IntroGAN. |
| 资助项目 | National Key R&D Program of China[2021ZD0111901] ; Natural Science Foundation of China[U21B2025] ; Natural Science Foundation of China[U19B2036] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001221726400001 |
| 出版者 | ELSEVIER SCI LTD |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/38986]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Wang, Ruiping |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, CAS, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Chen,Wang, Ruiping,Shan, Shiguang,et al. Introspective GAN: Learning to grow a GAN for incremental generation and classification[J]. PATTERN RECOGNITION,2024,151:12. |
| APA | He, Chen,Wang, Ruiping,Shan, Shiguang,&Chen, Xilin.(2024).Introspective GAN: Learning to grow a GAN for incremental generation and classification.PATTERN RECOGNITION,151,12. |
| MLA | He, Chen,et al."Introspective GAN: Learning to grow a GAN for incremental generation and classification".PATTERN RECOGNITION 151(2024):12. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。