A multi-task framework for weather recognition | |
Li, Xuelong1; Wang, Zhigang2; Lu, Xiaoqiang1 | |
2017-10-23 | |
会议日期 | 2017-10-23 |
会议地点 | Mountain View, CA, United states |
DOI | 10.1145/3123266.3123382 |
页码 | 1318-1326 |
英文摘要 | Weather recognition is important in practice, while this task has not been thoroughly explored so far. The current trend of dealing with this task is treating it as a single classification problem, i.e., determining whether a given image belongs to a certain weather category or not. However, weather recognition differs significantly from traditional image classification, since several weather features may appear simultaneously. In this case, a simple classification result is insufficient to describe the weather condition. To address this issue, we propose to provide auxiliary weather related information for comprehensive weather description. Specifically, semantic segmentation of weather-cues, such as blue sky and white clouds, is exploited as an auxiliary task in this paper. Moreover, a convolutional neural network (CNN) based multi-task framework is developed which aims to concurrently tackle weather category classification task and weather-cues segmentation task. Due to the intrinsic relationships between these two tasks, exploring auxiliary semantic segmentation of weather-cues can also help to learn discriminative features for the classification task, and thus obtain superior accuracy. To verify the effectiveness of the proposed approach, extra segmentation masks of weather-cues are generated manually on an existing weather image dataset. Experimental results have demonstrated the superior performance of our approach. The enhanced dataset, source codes and pre-trained models are available at https://github.com/wzgwzg/Multitask-Weather. © 2017 ACM. |
产权排序 | 1 |
会议录 | MM 2017 - Proceedings of the 2017 ACM Multimedia Conference |
会议录出版者 | Association for Computing Machinery, Inc |
语种 | 英语 |
ISBN号 | 9781450349062 |
内容类型 | 会议论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/29420] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
作者单位 | 1.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi; 710019, China 2.School of Computer Science, Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an, Shaanxi; 710072, China |
推荐引用方式 GB/T 7714 | Li, Xuelong,Wang, Zhigang,Lu, Xiaoqiang. A multi-task framework for weather recognition[C]. 见:. Mountain View, CA, United states. 2017-10-23. |
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