@inproceedings{bc3478ee329541b983ab136d81fb5144,
title = "DNN Flow: DNN feature pyramid based image matching",
abstract = "Image matching especially in category level is a challenge but important problem in vision. The advance of image matching largely depends on the advance of image features. In viewing recent success of learned image feature by DNN, we propose an image matching algorithm based on DNN feature pyramid, named as DNN Flow. The nature of DNN feature pyramid in detecting different level patterns makes it is suitable to match two images in a coarse to fine manner, where top level coarsely matches two images in object level, middle level matches two images in part level, and low level finely matches two images in pixel level. The coarse to fine matching based on DNN feature pyramid is formulated as a series of optimization problems considering the guidance from top level. Extensive experiments demonstrate the superiority of DNN Flow in image matching under challenge variations.",
author = "Wei Yu and Kuiyuan Yang and Yalong Bai and Hongxun Yao and Yong Rui",
note = "Publisher Copyright: {\textcopyright} 2014. The copyright of this document resides with its authors.; 25th British Machine Vision Conference, BMVC 2014 ; Conference date: 01-09-2014 Through 05-09-2014",
year = "2014",
doi = "10.5244/c.28.109",
language = "英语",
isbn = "1901725529",
series = "BMVC 2014 - Proceedings of the British Machine Vision Conference 2014",
publisher = "British Machine Vision Association, BMVA",
editor = "Michel Valstar and Andrew French and Tony Pridmore",
booktitle = "BMVC 2014 25th British Machine Vision Conference 2014",
}