Deep Semantic Reconstruction Hashing for Similarity Retrieval

doi:10.1109/TCSVT.2020.2974768

CASIA OpenIR > 模式识别实验室

	Deep Semantic Reconstruction Hashing for Similarity Retrieval
	Wang, Yunbo1,2 ; Ou, Xianfeng 3; Liang, Jian4 ; Sun, Zhenan1,2,5
发表期刊	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
ISSN	1051-8215
	2021
卷号	31 期号:1 页码:387-400
通讯作者	Sun, Zhenan(znsun@nlpr.ia.ac.cn)
摘要	Hashing has shown enormous potentials in preserving semantic similarity for large-scale data retrieval. Existing methods widely retain the similarity within two binary codes towards their discrete semantic affinity, i.e., 1 or -1. However, such a discrete reconstruction approach has obvious drawbacks. First, two unrelated dissimilar samples would have similar binary codes when both of them are the most dissimilar with an anchor sample. Second, the fine-grained semantic similarity cannot be shown in the generated binary codes among data with multiple semantic concepts. Furthermore, existing approaches generally adopt a point-wise error-minimizing strategy to enforce the real-valued codes close to its associated discrete codes, resulting in the well-learned paired semantic similarity being unintentionally damaged when performing quantization. To address these issues, we propose a novel deep hashing method with pairwise similarity-preserving quantization constraint, termed Deep Semantic Reconstruction Hashing (DSRH), which defines a high-level semantic affinity within each data pair to learn compact binary codes. Specifically, DSRH is expected to learn the specific binary codes whose similarity can reconstruct their high-level semantic similarity. Besides, we adopt a pairwise similarity-preserving quantization constraint instead of the traditional point-wise quantization technique, which is conducive to maintain the well-learned paired semantic similarity when performing quantization. Extensive experiments are conducted on four representative image retrieval benchmarks, and the proposed DSRH outperforms the state-of-the-art deep-learning methods with respect to different evaluation metrics.
关键词	Semantics Quantization (signal) Binary codes Image reconstruction Hamming distance Marine vehicles Airplanes Deep hashing high-level semantic similarity similarity-preserving quantization similarity retrieval
DOI	10.1109/TCSVT.2020.2974768
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2016YFB1001000] ; National Key Research and Development Program of China[2016YFB1001001] ; National Key Research and Development Program of China[2017YFC0821602] ; National Natural Science Foundation of China[U1836217] ; National Natural Science Foundation of China[61427811] ; National Natural Science Foundation of China[61573360] ; National Natural Science Foundation of China[61721004]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000607384300030
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	图像视频处理与分析
引用统计	被引频次：32[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/42557
专题	模式识别实验室
通讯作者	Sun, Zhenan
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Hunan Inst Sci & Technol, Sch Sci Informat & Engn, Yueyang 414006, Peoples R China 4.Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117583, Singapore 5.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Wang, Yunbo,Ou, Xianfeng,Liang, Jian,et al. Deep Semantic Reconstruction Hashing for Similarity Retrieval[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2021,31(1):387-400.
APA	Wang, Yunbo,Ou, Xianfeng,Liang, Jian,&Sun, Zhenan.(2021).Deep Semantic Reconstruction Hashing for Similarity Retrieval.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,31(1),387-400.
MLA	Wang, Yunbo,et al."Deep Semantic Reconstruction Hashing for Similarity Retrieval".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 31.1(2021):387-400.