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AHDet: A dynamic coarse-to-fine gaze strategy for active object detection

文献类型：期刊论文

作者Xu, Nuo1,2; Huo, Chunlei1,2; Zhang, Xin1,2; Pan, Chunhong2
刊名NEUROCOMPUTING
出版日期2022-06-28
卷号491页码:522-532
ISSN号0925-2312
关键词Object detection Active object detection Deep reinforcement learning Convolutional neural networks
DOI10.1016/j.neucom.2021.12.030
通讯作者Huo, Chunlei(clhuo@nlpr.ia.ac.cn)
英文摘要In the work setting of deep learning, most of the neural networks employed for visual object detection in recent years are based on bounding box regression. The performance of active detectors through multistep decision-making is limited by the rough model design. However, from the perspective of cognitive science, the recognition in the human visual system is a decision process from coarse to fine. Based on the theory of ``see the forest first, then the trees", this paper proposes a dynamic coarse-to-fine gaze strategy for active object detection, named AHDet, which takes the key points as the realization carrier of the coarse-to-fine concept. The detection process is divided into two steps, AIM and HIT. In the step of AIM, the positioning and prior bounding boxes for objects are given by detecting the center points, referring to the first glance. In the step of HIT, bounding boxes are dynamically adjusted to obtain compact bounding boxes with the help of the corner points, referring to the careful observation. With the design of the two-step coarse-to-fine gaze process, AHDet outperforms traditional approaches. A series of experiments performed on MS-COCO and PASCAL VOC dataset demonstrate the advantages of AHDet. (C) 2021 Elsevier B.V. All rights reserved.
资助项目National Key Research and Development Program of China[2018AAA0100400] ; National Natural Science Foundation of China[62071466] ; National Natural Science Foundation of China[91438105] ; National Natural Science Foundation of China[62076242] ; National Natural Science Foundation of China[61976208]
WOS研究方向Computer Science
语种英语
出版者ELSEVIER
WOS记录号WOS:000830181200010
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/49839]  
专题自动化研究所_模式识别国家重点实验室_遥感图像处理团队
通讯作者Huo, Chunlei
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Xu, Nuo,Huo, Chunlei,Zhang, Xin,et al. AHDet: A dynamic coarse-to-fine gaze strategy for active object detection[J]. NEUROCOMPUTING,2022,491:522-532.
APA Xu, Nuo,Huo, Chunlei,Zhang, Xin,&Pan, Chunhong.(2022).AHDet: A dynamic coarse-to-fine gaze strategy for active object detection.NEUROCOMPUTING,491,522-532.
MLA Xu, Nuo,et al."AHDet: A dynamic coarse-to-fine gaze strategy for active object detection".NEUROCOMPUTING 491(2022):522-532.

入库方式： OAI收割

来源：自动化研究所

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