中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control

文献类型：期刊论文

作者Chen, Shu-Yu1; Liu, Feng-Lin1; Lai, Yu-Kun2; Rosin, Paul L.2; Li, Chunpeng1; Fu, Hongbo3; Gao, Lin1
刊名ACM TRANSACTIONS ON GRAPHICS
出版日期2021-08-01
卷号40期号:4页码:15
ISSN号0730-0301
关键词Deep image generation face editing image disentangling sketch-based interfaces
DOI10.1145/3450626.3459760
英文摘要Recent facial image synthesis methods have been mainly based on conditional generative models. Sketch-based conditions can effectively describe the geometry of faces, including the contours of facial components, hair structures, as well as salient edges (e.g., wrinkles) on face surfaces but lack effective control of appearance, which is influenced by color, material, lighting condition, etc. To have more control of generated results, one possible approach is to apply existing disentangling works to disentangle face images into geometry and appearance representations. However, existing disentangling methods are not optimized for human face editing, and cannot achieve fine control of facial details such as wrinkles. To address this issue, we propose DeepFaceEditing, a structured disentanglement framework specifically designed for face images to support face generation and editing with disentangled control of geometry and appearance. We adopt a local-to-global approach to incorporate the face domain knowledge: local component images are decomposed into geometry and appearance representations, which are fused consistently using a global fusion module to improve generation quality. We exploit sketches to assist in extracting a better geometry representation, which also supports intuitive geometry editing via sketching. The resulting method can either extract the geometry and appearance representations from face images, or directly extract the geometry representation from face sketches. Such representations allow users to easily edit and synthesize face images, with decoupled control of their geometry and appearance. Both qualitative and quantitative evaluations show the superior detail and appearance control abilities of our method compared to state-of-the-art methods.
资助项目National Natural Science Foundation of China[61872440] ; National Natural Science Foundation of China[62061136007] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-STS-ZDTP-070] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-STS-QYZD-129] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-STS-QYZD-2021-11-001] ; Royal Society Newton Advanced Fellowship[NAF\R2\192151] ; Youth Innovation Promotion Association CAS ; Beijing Program for International S&T Cooperation Project[Z191100001619003] ; HK-SAR RGC General Research Fund[11212119] ; City University of Hong Kong (SCM ACIM Collaborative Research Fellowship)
WOS研究方向Computer Science
语种英语
出版者ASSOC COMPUTING MACHINERY
WOS记录号WOS:000674930900056
源URL[http://119.78.100.204/handle/2XEOYT63/17284]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Chen, Shu-Yu
作者单位1.Chinese Acad Sci, Beijing Key Lab Mobile Comp & Pervas Device, Inst Comp Technol, Beijing, Peoples R China
2.Cardiff Univ, Sch Comp Sci & Informat, Cardiff, Wales
3.City Univ Hong Kong, Sch Creat Media, Hong Kong, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Shu-Yu,Liu, Feng-Lin,Lai, Yu-Kun,et al. DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control[J]. ACM TRANSACTIONS ON GRAPHICS,2021,40(4):15.
APA Chen, Shu-Yu.,Liu, Feng-Lin.,Lai, Yu-Kun.,Rosin, Paul L..,Li, Chunpeng.,...&Gao, Lin.(2021).DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control.ACM TRANSACTIONS ON GRAPHICS,40(4),15.
MLA Chen, Shu-Yu,et al."DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control".ACM TRANSACTIONS ON GRAPHICS 40.4(2021):15.

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。