Heterogeneous Avatar Synthesis Based on Disentanglement of Topology and Rendering
Gao Nan; Zhi Zeng; GuiXuan Zhang; ShuWu Zhang
2022-12
会议名称The 16th Asian Conference on Computer Vision
会议日期2022-12-4
会议地点macao
出版地springer
摘要

There are obviously structural and color discrepancies among different heterogeneous domains. In this paper, we explore the challenging heterogeneous avatar synthesis (HAS) task considering topology and rendering transfer. HAS transfers the topology as well as rendering styles of the referenced face to the source face, to produce high-fidelity heterogeneous avatars. Specifically, first, we utilize a Rendering Transfer Network (RT-Net) to render the grayscale source face based on the color palette of the referenced face. The grayscale features and color style are injected into RT-Net based on adaptive feature modulation. Second, we apply a Topology Transfer Network (TT-Net) to conduct heterogeneous facial topology transfer, where the image content of RT-Net is transferred based on AdaIN controlled by heterogeneous identity embedding. Comprehensive experimental results show that the disentanglement of rendering and topology is beneficial to the HAS task, and our HASNet has comparable performance compared with other state-of-the-art methods.

关键词face generation
学科门类工学
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收录类别EI
语种英语
七大方向——子方向分类计算机图形学与虚拟现实
国重实验室规划方向分类视觉信息处理
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文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/57440
专题数字内容技术与服务研究中心_版权智能与文化计算
作者单位Institute of Automation Chinese Academy of Sciences, Beijing, China
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
Gao Nan,Zhi Zeng,GuiXuan Zhang,et al. Heterogeneous Avatar Synthesis Based on Disentanglement of Topology and Rendering[C]. springer,2022.
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