Attributed object detection based on natural language processing
ZHANG Xu, WANG Shengjin
State Key Laboratory of Intelligent Technology and System, National Laboratory for Information Science and Technology, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
Abstract：This paper addresses the problem of localizing an attributed object, such as "abandoned car", in images. Since one object may have tens or even hundreds of non-exclusive attributes, the main difficulties of attributed object detection are manually collecting training images and labeling the bounding boxes for a large number of attributed objects. This attributed object detector extends the object detector with an attributed object classifier. The attributed object classifier is trained by images from the Internet and labeling information gathered by the object detector and a natural language processing tool. An attributed object detection dataset was developed to evaluate the attributed object detectors. Tests show that this attributed object detector has good performance gains of 30% for the mean average precision compared to generic object detectors.
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ZHANG Xu, WANG Shengjin. Attributed object detection based on natural language processing. Journal of Tsinghua University(Science and Technology), 2016, 56(11): 1137-1142.
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