| Transductive Face Sketch-Photo Synthesis | |
Wang, Nannan1; Tao, Dacheng2,3 ; Gao, Xinbo1; Li, Xuelong4; Li, Jie1
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| 2013-09-01 | |
| 发表期刊 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
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| 卷号 | 24期号:9页码:1364-1376 |
| 摘要 | Face sketch-photo synthesis plays a critical role in many applications, such as law enforcement and digital entertainment. Recently, many face sketch-photo synthesis methods have been proposed under the framework of inductive learning, and these have obtained promising performance. However, these inductive learning-based face sketch-photo synthesis methods may result in high losses for test samples, because inductive learning minimizes the empirical loss for training samples. This paper presents a novel transductive face sketch-photo synthesis method that incorporates the given test samples into the learning process and optimizes the performance on these test samples. In particular, it defines a probabilistic model to optimize both the reconstruction fidelity of the input photo (sketch) and the synthesis fidelity of the target output sketch (photo), and efficiently optimizes this probabilistic model by alternating optimization. The proposed transductive method significantly reduces the expected high loss and improves the synthesis performance for test samples. Experimental results on the Chinese University of Hong Kong face sketch data set demonstrate the effectiveness of the proposed method by comparing it with representative inductive learning-based face sketch-photo synthesis methods. |
| 文章类型 | Article |
| 关键词 | Probabilistic Graph Model Quadratic Programming Sketch-photo Synthesis Transductive Learning |
| WOS标题词 | Science & Technology ; Technology |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | SPARSE REPRESENTATION ; RECOGNITION ; IMAGE ; RECONSTRUCTION ; TRANSFORMATION ; INFORMATION ; ENSEMBLE |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000325980900002 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/23197 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Xidian Univ, Sch Elect Engn, VIPS Lab, Xian 710071, Peoples R China 2.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Ultimo, NSW 2007, Australia 3.Univ Technol Sydney, Fac Engn & Informat Technol, Ultimo, NSW 2007, Australia 4.Chinese Acad Sci, Ctr OPT IMagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Nannan,Tao, Dacheng,Gao, Xinbo,et al. Transductive Face Sketch-Photo Synthesis[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2013,24(9):1364-1376. |
| APA | Wang, Nannan,Tao, Dacheng,Gao, Xinbo,Li, Xuelong,&Li, Jie.(2013).Transductive Face Sketch-Photo Synthesis.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,24(9),1364-1376. |
| MLA | Wang, Nannan,et al."Transductive Face Sketch-Photo Synthesis".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 24.9(2013):1364-1376. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Transductive Face Sk（2307KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY | 请求全文 | |
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