Saliency detection in 360° Videos

doi:10.1007/978-3-030-01234-2_30

	Saliency detection in 360° Videos
	Zhang, Ziheng; Xu, Yanyu; Yu, Jingyi; Gao, Shenghua
	2018
会议录名称	15TH EUROPEAN CONFERENCE ON COMPUTER VISION, ECCV 2018
卷号	11211 LNCS
页码	504-520
发表状态	已发表
DOI	10.1007/978-3-030-01234-2_30
摘要	This paper presents a novel spherical convolutional neural network based scheme for saliency detection for 360° videos. Specifically, in our spherical convolution neural network definition, kernel is defined on a spherical crown, and the convolution involves the rotation of the kernel along the sphere. Considering that the 360° videos are usually stored with equirectangular panorama, we propose to implement the spherical convolution on panorama by stretching and rotating the kernel based on the location of patch to be convolved. Compared with existing spherical convolution, our definition has the parameter sharing property, which would greatly reduce the parameters to be learned. We further take the temporal coherence of the viewing process into consideration, and propose a sequential saliency detection by leveraging a spherical U-Net. To validate our approach, we construct a large-scale 360° videos saliency detection benchmark that consists of 104 360° videos viewed by 20+ human subjects. Comprehensive experiments validate the effectiveness of our spherical U-net for 360° video saliency detection. © Springer Nature Switzerland AG 2018.
会议地点	Munich, Germany
收录类别	EI ; CPCI ; CPCI-S
资助项目	National Natural Science Foundation of China[61502304]
出版者	Springer Verlag
EI入藏号	20184305977607
EI主题词	Computer vision ; Convolution ; Neural networks
EI分类号	Information Theory and Signal Processing:716.1 ; Computer Applications:723.5
原始文献类型	Conference article (CA)
引用统计	正在获取...
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/28663
专题	信息科学与技术学院_博士生信息科学与技术学院_PI研究组_虞晶怡组信息科学与技术学院_PI研究组_高盛华组信息科学与技术学院_硕士生
通讯作者	Gao, Shenghua
作者单位	ShanghaiTech University, Shanghai, China
第一作者单位	上海科技大学
通讯作者单位	上海科技大学
第一作者的第一单位	上海科技大学
推荐引用方式 GB/T 7714	Zhang, Ziheng,Xu, Yanyu,Yu, Jingyi,et al. Saliency detection in 360° Videos[C]:Springer Verlag,2018:504-520.