Attention Weighted Local Descriptors-Reference-Cited by-同舟云学术

Attention Weighted Local Descriptors

Author:

Wang Changwei¹^ORCID,Xu Rongtao¹^ORCID,Lu Ke²^ORCID,Xu Shibiao³^ORCID,Meng Weiliang¹^ORCID,Zhang Yuyang⁴^ORCID,Fan Bin⁵^ORCID,Zhang Xiaopeng¹^ORCID

Affiliation:

1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

2. School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China

3. School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China

4. Thunder Software Technology Company, Ltd., Chengdu, China

5. School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China

Funder

National Natural Science Foundation of China

Open Research Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences

National Laboratory of Pattern Recognition

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

Reference83 articles.

1. Three things everyone should know to improve object retrieval;arandjelovi?;Proc IEEE Conf Comput Vis Pattern Recognit,2012

2. Supervised hashing with kernels;liu;Proc IEEE Conf Comput Vis Pattern Recognit,2012

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

4. DomainFeat: Learning Local Features With Domain Adaptation;IEEE Transactions on Circuits and Systems for Video Technology;2024-01