Institute of Computing Technology, Chinese Academy IR
Deep Supervised Hashing for Fast Image Retrieval | |
Liu, Haomiao1,2; Wang, Ruiping1,2; Shan, Shiguang1,2; Chen, Xilin1,2 | |
2019-09-01 | |
发表期刊 | INTERNATIONAL JOURNAL OF COMPUTER VISION |
ISSN | 0920-5691 |
卷号 | 127期号:9页码:1217-1234 |
摘要 | In this paper, we present a new hashing method to learn compact binary codes for highly efficient image retrieval on large-scale datasets. While the complex image appearance variations still pose a great challenge to reliable retrieval, in light of the recent progress of Convolutional Neural Networks (CNNs) in learning robust image representation on various vision tasks, this paper proposes a novel Deep Supervised Hashing method to learn compact similarity-preserving binary code for the huge body of image data. Specifically, we devise a CNN architecture that takes pairs/triplets of images as training inputs and encourages the output of each image to approximate discrete values (e.g. +1). To this end, the loss functions are elaborately designed to maximize the discriminability of the output space by encoding the supervised information from the input image pairs/triplets, and simultaneously imposing regularization on the real-valued outputs to approximate the desired discrete values. For image retrieval, new-coming query images can be easily encoded by forward propagating through the network and then quantizing the network outputs to binary codes representation. Extensive experiments on three large scale datasets CIFAR-10, NUS-WIDE, and SVHN show the promising performance of our method compared with the state-of-the-arts. |
关键词 | Image retrieval Hashing Convolutional network Contrastive loss Triplet ranking loss |
DOI | 10.1007/s11263-019-01174-4 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | 973 Program[2015CB351802] ; Natural Science Foundation of China[61390511] ; Natural Science Foundation of China[61772500] ; Frontier Science Key Research Project CAS[QYZDJ-SSW-JSC009] ; Youth Innovation Promotion Association CAS[2015085] |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000477642300003 |
出版者 | SPRINGER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/4481 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Wang, Ruiping |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Haomiao,Wang, Ruiping,Shan, Shiguang,et al. Deep Supervised Hashing for Fast Image Retrieval[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2019,127(9):1217-1234. |
APA | Liu, Haomiao,Wang, Ruiping,Shan, Shiguang,&Chen, Xilin.(2019).Deep Supervised Hashing for Fast Image Retrieval.INTERNATIONAL JOURNAL OF COMPUTER VISION,127(9),1217-1234. |
MLA | Liu, Haomiao,et al."Deep Supervised Hashing for Fast Image Retrieval".INTERNATIONAL JOURNAL OF COMPUTER VISION 127.9(2019):1217-1234. |
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