A2-RL: Aesthetics Aware Reinforcement Learning for Image Cropping
文献类型：会议论文
| 作者 | Li, Debang2,3 ; Wu, Huikai2,3; Zhang, Junge2,3; Huang, Kaiqi1,2,3
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| 出版日期 | 2018-06 |
| 会议日期 | 18-23 June 2018 |
| 会议地点 | Salt Lake City, UT, USA |
| 页码 | 8193-8201 |
| 英文摘要 | Image cropping aims at improving the aesthetic quality of images by adjusting their composition. Most weakly supervised cropping methods (without bounding box supervision) rely on the sliding window mechanism. The sliding window mechanism requires fixed aspect ratios and limits the cropping region with arbitrary size. Moreover, the sliding window method usually produces tens of thousands of windows on the input image which is very time-consuming. Motivated by these challenges, we firstly formulate the aesthetic image cropping as a sequential decision-making process and propose a weakly supervised Aesthetics Aware Reinforcement Learning (A2-RL) framework to address this problem. Particularly, the proposed method develops an aesthetics aware reward function which especially benefits image cropping. Similar to human's decision making, we use a comprehensive state representation including both the current observation and the historical experience. We train the agent using the actor-critic architecture in an end-to-end manner. The agent is evaluated on several popular unseen cropping datasets. Experiment results show that our method achieves the state-of-the-art performance with much fewer candidate windows and much less time compared with previous weakly supervised methods. |
| 源文献作者 | IEEE ; CVF |
| 会议录 | Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2018
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| 会议录出版者 | IEEE |
| 语种 | 英语 |
| URL标识 | 查看原文 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/44362]  |
| 专题 | 智能系统与工程 |
| 通讯作者 | Huang, Kaiqi |
| 作者单位 | 1.University of Chinese Academy of Sciences, Beijing, China 2.CAS Center for Excellence in Brain Science and Intelligence Technology, Beijing, China 3.CRIPAC & NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Li, Debang,Wu, Huikai,Zhang, Junge,et al. A2-RL: Aesthetics Aware Reinforcement Learning for Image Cropping[C]. 见:. Salt Lake City, UT, USA. 18-23 June 2018. |
入库方式： OAI收割
来源：自动化研究所
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