Knowledge Commons of Institute of Automation,CAS
Mixed Supervised Object Detection with Robust Objectness Transfer | |
Li Y(李岩)1,2![]() ![]() ![]() | |
发表期刊 | IEEE Transactions on Pattern Analysis and Machine Intelligence
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2019-03 | |
卷号 | 41期号:3页码:639-653 |
摘要 | In this paper, we consider the problem of leveraging existing fully labeled categories to improve the weakly supervised detection (WSD) of new object categories, which we refer to as mixed supervised detection (MSD). Different from previous MSD methods that directly transfer the pre-trained object detectors from existing categories to new categories, we propose a more reasonable and robust objectness transfer approach for MSD. In our framework, we first learn domain-invariant objectness knowledge from the existing fully labeled categories. The knowledge is modeled based on invariant features that are robust to the distribution |
关键词 | Weakly Supervised Detection Mixed Supervised Detection Robust Objectness Transfer |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000458168800009 |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23345 |
专题 | 复杂系统认知与决策实验室_智能系统与工程 模式识别实验室 |
通讯作者 | Huang KQ(黄凯奇) |
作者单位 | 1.中国科学院自动化研究所 2.University of Chinese Academy of Sciences 3.Computing, School of Science and Engineering, Univerisity of Dundee, UK 4.CAS Center for Excellence in Brain Science and Intelligence Technology |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Li Y,Zhang JG,Huang KQ,et al. Mixed Supervised Object Detection with Robust Objectness Transfer[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2019,41(3):639-653. |
APA | Li Y,Zhang JG,Huang KQ,&Zhang JG.(2019).Mixed Supervised Object Detection with Robust Objectness Transfer.IEEE Transactions on Pattern Analysis and Machine Intelligence,41(3),639-653. |
MLA | Li Y,et al."Mixed Supervised Object Detection with Robust Objectness Transfer".IEEE Transactions on Pattern Analysis and Machine Intelligence 41.3(2019):639-653. |
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