Weakly-Supervised Object Localization by Cutting Background with Deep Reinforcement Learning | |
Wu Zheng1,2,4; Zhaoxiang Zhang1,2,3,4 | |
2018-08 | |
会议日期 | 2018-08 |
会议地点 | Nanjing, China |
关键词 | Weakly-supervised Object Localization, Deep Reinforcement Learning, Convolutional Neural Network |
卷号 | vol 11013 |
DOI | https://doi.org/10.1007/978-3-319-97310-4_24 |
英文摘要 | Weakly-supervised object localization only depends on image-level labels to obtain object locations and attracts more attention recently. Taking inspiration from the human visual mechanism that human searches and localizes the region of interest by shrinking the view from a wide range and ignoring the unrelated background gradually, we propose a novel weakly-supervised localization method of cutting background of an object iteratively to achieve object localization with deep reinforcement learning. This approach can train an agent as a detector, which searches through the image and tries to cut off all regions unrelated to classification performance. An effective refinement approach is also proposed, which generates a heat-map by sum-pooling all feature maps to refine the location cropped by the agent. As a result, by combining the top-down cutting process and the bottom-up evidence for refinement, we can achieve a good performance on object localization in only several steps. To the best of our knowledge, this may be the first attempt to apply deep reinforcement learning to weakly-supervised object localization. We perform our experiments on PASCAL VOC dataset and the results show our method is effective. |
会议录 | Lecture Notes in Computer Science |
会议录出版者 | Springer |
会议录出版地 | Cham |
语种 | 英语 |
URL标识 | 查看原文 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/23860] |
专题 | 自动化研究所_智能感知与计算研究中心 |
通讯作者 | Zhaoxiang Zhang |
作者单位 | 1.Center for Research on Intelligent Perception and Computing, CASIA, China 2.National Laboratory of Pattern Recognition, CASIA, China 3.CAS Center for Excellence in Brain Science and Intelligence Technology, China 4.University of Chinese Academy of Sciences, China |
推荐引用方式 GB/T 7714 | Wu Zheng,Zhaoxiang Zhang. Weakly-Supervised Object Localization by Cutting Background with Deep Reinforcement Learning[C]. 见:. Nanjing, China. 2018-08. |
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