Spectral attribute learning for visual regression
文献类型：期刊论文
| 作者 | Chen, Ke1; Jia, Kui2; Zhang, Zhaoxiang3 ; Kamarainen, Joni-Kristian1; Kui Jia
|
| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 2017-06-01 |
| 卷号 | 66期号:0页码:74-81 |
| 关键词 | Facial Age Estimation Crowd Counting Head Pose Estimation Spectral Learning Attributes Regression |
| DOI | 10.1016/j.patcog.2017.01.009 |
| 文献子类 | Article |
| 英文摘要 | A number of computer vision problems such as facial age estimation, crowd counting and pose estimation can be solved by learning regression mapping on low-level imagery features. We show that visual regression can be substantially improved by two-stage regression where imagery features are first mapped to an attribute space which explicitly models latent correlations across continuously-changing output. We propose an approach to automatically discover "spectral attributes" which avoids manual work required for defining hand-crafted attribute representations. Visual attribute regression outperforms direct visual regression and our spectral attribute visual regression achieves state-of-the-art accuracy in multiple applications. |
| WOS关键词 | AGE ESTIMATION ; PERSON REIDENTIFICATION |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000397371800009 |
| 资助机构 | Academy of Finland(267581 ; 298700) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/14035]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Kui Jia |
| 作者单位 | 1.Tampere Univ Technol, Dept Signal Proc, Tampere, Finland 2.South China Univ Technol, Sch Elect & Informat Engn, Guangzhou, Guangdong, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Ke,Jia, Kui,Zhang, Zhaoxiang,et al. Spectral attribute learning for visual regression[J]. PATTERN RECOGNITION,2017,66(0):74-81. |
| APA | Chen, Ke,Jia, Kui,Zhang, Zhaoxiang,Kamarainen, Joni-Kristian,&Kui Jia.(2017).Spectral attribute learning for visual regression.PATTERN RECOGNITION,66(0),74-81. |
| MLA | Chen, Ke,et al."Spectral attribute learning for visual regression".PATTERN RECOGNITION 66.0(2017):74-81. |
入库方式： OAI收割
来源：自动化研究所
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