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Learning Scene Attribute for Scene Recognition

文献类型：期刊论文

作者Zeng, Haitao1,2; Song, Xinhang2; Chen, Gongwei2; Jiang, Shuqiang2,3
刊名IEEE TRANSACTIONS ON MULTIMEDIA
出版日期2020-06-01
卷号22期号:6页码:1519-1530
关键词Feature extraction Visualization Semantics Context modeling Image recognition Computer vision Aggregates Scene recognition scene attribute
ISSN号1520-9210
DOI10.1109/TMM.2019.2944241
英文摘要Scene recognition has been a challenging task in the field of computer vision and multimedia for a long time. The current scene recognition works often extract object features and scene features through CNN, and combine these two types of features to obtain complementary and discriminative scene representations. However, when the scene categories are visually similar, the object features might lack of discriminations. Therefore, it may be debatable to consider only object features. In contrast to the existing works, in this paper, we discuss the discrimination of scene attributes in local regions and utilize scene attributes as the complementary features of object and scene features. We extract these visual features from two individual CNN branches, one extracting the global features of the image while the other extracting the features of local regions. Through contextual modeling framework, we aggregate these features and generate more discriminative scene representations, which achieve better performance than the feature aggregation of object and scene. Moreover, we achieve the new state-of-the-art performance on both standard scene recognition benchmarks by aggregating more complementary visual features: MIT67 (88.06%) and SUN397 (74.12%).
资助项目National Natural Science Foundation of China[61532018] ; National Natural Science Foundation of China[61902378] ; Beijing Natural Science Foundation[L182054] ; Beijing Natural Science Foundation[Z190020] ; National Program for Special Support of Eminent Professionals ; National Program for Support of Top-notch Young Professionals ; National Postdoctoral Program for Innovative Talents[BX201700255] ; China Postdoctoral Science Foundation[2018M631583]
WOS研究方向Computer Science ; Telecommunications
语种英语
WOS记录号WOS:000538033100012
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/15252]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Jiang, Shuqiang
作者单位1.China Univ Min & Technol, Beijing 100083, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Zeng, Haitao,Song, Xinhang,Chen, Gongwei,et al. Learning Scene Attribute for Scene Recognition[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2020,22(6):1519-1530.
APA Zeng, Haitao,Song, Xinhang,Chen, Gongwei,&Jiang, Shuqiang.(2020).Learning Scene Attribute for Scene Recognition.IEEE TRANSACTIONS ON MULTIMEDIA,22(6),1519-1530.
MLA Zeng, Haitao,et al."Learning Scene Attribute for Scene Recognition".IEEE TRANSACTIONS ON MULTIMEDIA 22.6(2020):1519-1530.

入库方式： OAI收割

来源：计算技术研究所

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