CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术
Label Distribution-Based Facial Attractiveness Computation by Deep Residual Learning
Fan, Yang-Yu1; Liu, Shu1; Li, Bo1; Guo, Zhe1; Samal, Ashok2; Wan, Jun3,4; Li, Stan Z.3,4
Source PublicationIEEE TRANSACTIONS ON MULTIMEDIA
ISSN1520-9210
2018-08-01
Volume20Issue:8Pages:2196-2208
Corresponding AuthorLiu, Shu(liushu0922@mail.nwpu.edu.cn)
AbstractTwo key challenges lie in the facial attractiveness computation research: the lack of discriminative face representations, and the scarcity of sufficient and complete training data. Motivated by recent promising work in face recognition using deep neural networks to learn effective features, the first challenge is expected to be addressed from a deep learning point of view. A very deep residual network is utilized to enable automatic learning of hierarchical aesthetics representation. The inspiration to deal with the second challenge comes from the natural representation of the training data, where each training face can be associated with a label (score) distribution given by human raters rather than a single label (average score). This paper, therefore, recasts facial attractiveness computation as a label distribution learning problem. Integrating these two ideas, an end-to-end attractiveness learning framework is established. We also perform feature-level fusion by incorporating the low-level geometric features to further improve the computational performance. Extensive experiments are conducted on a standard benchmark, the SCUT-FBP dataset, where our approach shows significant advantages over the other state-of-the-art work.
KeywordFacial attractiveness computation deep residual network label distribution feature fusion SCUT-FBP
DOI10.1109/TMM.2017.2780762
WOS KeywordBEAUTY ; PREDICTION
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61402371] ; National Natural Science Foundation of China[61461025] ; National Natural Science Foundation of China[61702462] ; National Natural Science Foundation of China[61502491] ; Science and Technology Innovation Engineering Plan in Shaanxi Province of China[2013SZS15-K02] ; Natural Science Basic Research Plan in Shaanxi Province of China[2017JM6008] ; National Natural Science Foundation of China[61402371] ; National Natural Science Foundation of China[61461025] ; National Natural Science Foundation of China[61702462] ; National Natural Science Foundation of China[61502491] ; Science and Technology Innovation Engineering Plan in Shaanxi Province of China[2013SZS15-K02] ; Natural Science Basic Research Plan in Shaanxi Province of China[2017JM6008]
Funding OrganizationNational Natural Science Foundation of China ; Science and Technology Innovation Engineering Plan in Shaanxi Province of China ; Natural Science Basic Research Plan in Shaanxi Province of China
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000439378600022
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:12[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19773
Collection模式识别国家重点实验室_生物识别与安全技术
Corresponding AuthorLiu, Shu
Affiliation1.Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Shaanxi, Peoples R China
2.Univ Nebraska, Dept Comp Sci & Engn, Lincoln, NE 68588 USA
3.Chinese Acad Sci, Ctr Biometr & Secur Res, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Fan, Yang-Yu,Liu, Shu,Li, Bo,et al. Label Distribution-Based Facial Attractiveness Computation by Deep Residual Learning[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2018,20(8):2196-2208.
APA Fan, Yang-Yu.,Liu, Shu.,Li, Bo.,Guo, Zhe.,Samal, Ashok.,...&Li, Stan Z..(2018).Label Distribution-Based Facial Attractiveness Computation by Deep Residual Learning.IEEE TRANSACTIONS ON MULTIMEDIA,20(8),2196-2208.
MLA Fan, Yang-Yu,et al."Label Distribution-Based Facial Attractiveness Computation by Deep Residual Learning".IEEE TRANSACTIONS ON MULTIMEDIA 20.8(2018):2196-2208.
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