Knowledge Commons of Institute of Automation,CAS
Arbitrary Style Transfer via Multi-Adaptation Network | |
Deng, Yingying1,2; Tang, Fan2; Dong, Weiming2,3; Sun, Wen1,2; Huang, Feiyue4; Xu, Changsheng2,3 | |
2020 | |
会议名称 | International Conference on Multimedia |
会议日期 | 2020-10 |
会议地点 | Vitual conference |
摘要 | Arbitrary style transfer is a significant topic with research value and application prospect. A desired style transfer, given a content image and referenced style painting, would render the content image with the color tone and vivid stroke patterns of the style painting while synchronously maintaining the detailed content structure information. Style transfer approaches would initially learn content and style representations of the content and style references and then generate the stylized images guided by these representations. In this paper, we propose the multi-adaptation network which involves two self-adaptation (SA) modules and one co-adaptation (CA) module: the SA modules adaptively disentangle the content and style representations, i.e., content SA module uses position-wise self-attention to enhance content representation and style SA module uses channel-wise self-attention to enhance style representation; the CA module rearranges the distribution of style representation based on content representation distribution by calculating the local similarity between the disentangled content and style features in a non-local fashion. Moreover, a new disentanglement loss function enables our network to extract main style patterns and exact content structures to adapt to various input images, respectively. Various qualitative and quantitative experiments demonstrate that the proposed multi-adaptation network leads to better results than the state-of-the-art style transfer methods. |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48626 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
通讯作者 | Tang, Fan; Sun, Wen |
作者单位 | 1.School of Artificial Intelligence, UCAS 2.NLPR, Institute of Automation, CAS 3.CASIA-LLVision Joint Lab 4.Youtu Lab, Tencent |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Deng, Yingying,Tang, Fan,Dong, Weiming,et al. Arbitrary Style Transfer via Multi-Adaptation Network[C],2020. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
[2]Arbitrary Style T(8978KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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。
修改评论