TSSD: Temporal Single-Shot Detector Based on Attention and LSTM
文献类型:会议论文
作者 | Xingyu Chen1,2; Zhengxing Wu1,2; Junzhi Yu1,2; Chen, Xingyu; Yu, Junzhi; Wu, Zhengxing |
出版日期 | 2018-10 |
会议日期 | 2018-10 |
会议地点 | Madrid, Spain |
英文摘要 | Temporal object detection has attracted significant attention, but most popular methods can not leverage the rich temporal information in video or robotic vision. Although many different algorithms have been developed for video detection task, real-time online approaches are frequently deficient. In this paper, based on attention mechanism and convolutional long short-term memory (ConvLSTM), we propose a temporal single-shot detector (TSSD) for robotic vision. Distinct from previous methods, we aim to temporally integrate pyramidal feature hierarchy using ConvLSTM, and design a novel structure including a high-level ConvLSTM unit as well as a low-level one (HL-LSTM) for multi-scale feature maps. Moreover, we develop a creative temporal analysis unit, namely, ConvLSTMbased attention and attention-based ConvLSTM (A&CL), in which the ConvLSTM-based attention is specially tailored |
源URL | [http://ir.ia.ac.cn/handle/173211/39067] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
通讯作者 | Zhengxing Wu; Wu, Zhengxing |
作者单位 | 1.Institute of Automation, Chinese Academy of Science 2.University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Xingyu Chen,Zhengxing Wu,Junzhi Yu,et al. TSSD: Temporal Single-Shot Detector Based on Attention and LSTM[C]. 见:. Madrid, Spain. 2018-10. |
入库方式: OAI收割
来源:自动化研究所
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