Structure-Aware Deep Learning for Product Image Classification
文献类型：期刊论文
| 作者 | Chen, Zhineng1 ; Al, Shanshan2; Jia, Caiyan2
|
| 刊名 | ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
 |
| 出版日期 | 2019-02-01 |
| 卷号 | 15期号:1页码:20 |
| 关键词 | Image classification category hierarchy convolutional neural network multi-class regression multi-task learning |
| ISSN号 | 1551-6857 |
| DOI | 10.1145/3231742 |
| 通讯作者 | Jia, Caiyan(cyjia@bjtu.edu.cn) |
| 英文摘要 | Automatic product image classification is a task of crucial importance with respect to the management of online retailers. Motivated by recent advancements of deep Convolutional Neural Networks (CNN) on image classification, in this work we revisit the problem in the context of product images with the existence of a predefined categorical hierarchy and attributes, aiming to leverage the hierarchy and attributes to improve classification accuracy. With these structure-aware clues, we argue that more advanced deep models could be developed beyond the flat one-versus-all classification performed by conventional CNNs. To this end, novel efforts of this work include a salient-sensitive CNN that gazes into the product foreground by inserting a dedicated spatial attention module; a multiclass regression-based refinement that is expected to predict more accurately by merging prediction scores from multiple preceding CNNs, each corresponding to a distinct classifier in the hierarchy; and a multitask deep learning architecture that effectively explores correlations among categories and attributes for categorical label prediction. Experimental results on nearly 1 million real-world product images basically validate the effectiveness of the proposed efforts individually and jointly, from which performance gains are observed. |
| WOS关键词 | ASSOCIATION |
| 资助项目 | National Natural Science Foundation of China[61772526] ; National Natural Science Foundation of China[61473030] ; National Key RD Plan of China[2017YFB1002804] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000459798100004 |
| 出版者 | ASSOC COMPUTING MACHINERY |
| 资助机构 | National Natural Science Foundation of China ; National Key RD Plan of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/25010]  |
| 专题 | 数字内容技术与服务研究中心_远程智能医疗 |
| 通讯作者 | Jia, Caiyan |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 2.Beijing Jiaotong Univ, 3 Shangyuancun Rd, Beijing 100044, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Zhineng,Al, Shanshan,Jia, Caiyan. Structure-Aware Deep Learning for Product Image Classification[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2019,15(1):20. |
| APA | Chen, Zhineng,Al, Shanshan,&Jia, Caiyan.(2019).Structure-Aware Deep Learning for Product Image Classification.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,15(1),20. |
| MLA | Chen, Zhineng,et al."Structure-Aware Deep Learning for Product Image Classification".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 15.1(2019):20. |
入库方式： OAI收割
来源：自动化研究所
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