ShanghaiTech University Knowledge Management System
Learning efficient text-to-image synthesis via interstage cross-sample similarity distillation | |
2021 | |
发表期刊 | SCIENCE CHINA-INFORMATION SCIENCES (IF:7.3[JCR-2023],5.8[5-Year]) |
ISSN | 1674-733X |
EISSN | 1869-1919 |
卷号 | 64期号:2 |
发表状态 | 已发表 |
DOI | 10.1007/s11432-020-2900-x |
摘要 | For a given text, previous text-to-image synthesis methods commonly utilize a multistage generation model to produce images with high resolution in a coarse-to-fine manner. However, these methods ignore the interaction among stages, and they do not constrain the consistent cross-sample relations of images generated in different stages. These deficiencies result in inefficient generation and discrimination. In this study, we propose an interstage cross-sample similarity distillation model based on a generative adversarial network (GAN) for learning efficient text-to-image synthesis. To strengthen the interaction among stages, we achieve interstage knowledge distillation from the refined stage to the coarse stages with novel interstage cross-sample similarity distillation blocks. To enhance the constraint on the cross-sample relations of the images generated at different stages, we conduct cross-sample similarity distillation among the stages. Extensive experiments on the Oxford-102 and Caltech-UCSD Birds-200-2011 (CUB) datasets show that our model generates visually pleasing images and achieves quantitatively comparable performance with state-of-the-art methods. |
关键词 | generative adversarial network (GAN) text-to-image synthesis knowledge distillation |
收录类别 | EI ; SCIE |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Information Systems ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000595379700001 |
出版者 | SCIENCE PRESS |
原始文献类型 | Article |
引用统计 | 正在获取...
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文献类型 | 期刊论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/127904 |
专题 | 信息科学与技术学院_硕士生 |
通讯作者 | Ma, Bingpeng |
作者单位 | 1.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China; 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Chinese Acad Sci CAS, Beijing 100190, Peoples R China; 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 4.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China |
第一作者单位 | 信息科学与技术学院 |
第一作者的第一单位 | 信息科学与技术学院 |
推荐引用方式 GB/T 7714 | Mao, Fengling,Ma, Bingpeng,Chang, Hong,et al. Learning efficient text-to-image synthesis via interstage cross-sample similarity distillation[J]. SCIENCE CHINA-INFORMATION SCIENCES,2021,64(2). |
APA | Mao, Fengling,Ma, Bingpeng,Chang, Hong,Shan, Shiguang,&Chen, Xilin.(2021).Learning efficient text-to-image synthesis via interstage cross-sample similarity distillation.SCIENCE CHINA-INFORMATION SCIENCES,64(2). |
MLA | Mao, Fengling,et al."Learning efficient text-to-image synthesis via interstage cross-sample similarity distillation".SCIENCE CHINA-INFORMATION SCIENCES 64.2(2021). |
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