A Deep Model for Partial Multi-label Image Classification with Curriculum-based Disambiguation
文献类型：期刊论文
| 作者 | Feng Sun; Ming-Kun Xie; Sheng-Jun Huang |
| 刊名 | Machine Intelligence Research
 |
| 出版日期 | 2024 |
| 卷号 | 21期号:4页码:801-814 |
| 关键词 | Partial multi-label image classification curriculum-based disambiguation consistency regularization label difficulty candidate label set. |
| ISSN号 | 2731-538X |
| DOI | 10.1007/s11633-023-1439-3 |
| 英文摘要 | In this paper, we study the partial multi-label (PML) image classification problem, where each image is annotated with a candidate label set consisting of multiple relevant labels and other noisy labels. Existing PML methods typically design a disambiguation strategy to filter out noisy labels by utilizing prior knowledge with extra assumptions, which unfortunately is unavailable in many real tasks. Furthermore, because the objective function for disambiguation is usually elaborately designed on the whole training set, it can hardly be optimized in a deep model with stochastic gradient descent (SGD) on mini-batches. In this paper, for the first time, we propose a deep model for PML to enhance the representation and discrimination ability. On the one hand, we propose a novel curriculum-based disambiguation strategy to progressively identify ground-truth labels by incorporating the varied difficulties of different classes. On the other hand, consistency regularization is introduced for model training to balance fitting identified easy labels and exploiting potential relevant labels. Extensive experimental results on the commonly used benchmark datasets show that the proposed method significantly outperforms the SOTA methods. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/58573]  |
| 专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
| 作者单位 | MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China |
| 推荐引用方式 GB/T 7714 | Feng Sun,Ming-Kun Xie,Sheng-Jun Huang. A Deep Model for Partial Multi-label Image Classification with Curriculum-based Disambiguation[J]. Machine Intelligence Research,2024,21(4):801-814. |
| APA | Feng Sun,Ming-Kun Xie,&Sheng-Jun Huang.(2024).A Deep Model for Partial Multi-label Image Classification with Curriculum-based Disambiguation.Machine Intelligence Research,21(4),801-814. |
| MLA | Feng Sun,et al."A Deep Model for Partial Multi-label Image Classification with Curriculum-based Disambiguation".Machine Intelligence Research 21.4(2024):801-814. |
入库方式： OAI收割
来源：自动化研究所
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