Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360 degrees Omnidirectional Image

doi:10.1109/TNNLS.2022.3233883

	Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360 degrees Omnidirectional Image
	Cong, Runmin 1,2; Huang, Ke 2,3; Lei, Jianjun 4; Zhao, Yao 2,3; Huang, Qingming 5,6,7; Kwong, Sam 8,9
	2023-01-09
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN	2162-237X
页码	13
摘要	Salient object detection (SOD) aims to determine the most visually attractive objects in an image. With the devel-opment of virtual reality (VR) technology, 360(?) omnidirectional image has been widely used, but the SOD task in 360(?) omni-directional image is seldom studied due to its severe distortions and complex scenes. In this article, we propose a multi-projection fusion and refinement network (MPFR-Net) to detect the salient objects in 360(?) omnidirectional image. Different from the existing methods, the equirectangular projection (EP) image and four corresponding cube-unfolding (CU) images are embedded into the network simultaneously as inputs, where the CU images not only provide supplementary information for EP image but also ensure the object integrity of cube-map projection. In order to make full use of these two projection modes, a dynamic weighting fusion (DWF) module is designed to adaptively integrate the features of different projections in a complementary and dynamic manner from the perspective of inter and intrafeatures. Furthermore,
关键词	360? omnidirectional image cube-unfolding (CU) dynamic weighting filtration and refinement (FR) salient object detection (SOD)
DOI	10.1109/TNNLS.2022.3233883
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2021ZD0112100] ; Beijing Nova Program[Z201100006820016] ; National Natural Science Foundation of China[62002014] ; National Natural Science Foundation of China[U1936212] ; National Natural Science Foundation of China[62120106009] ; National Natural Science Foundation of China[62236008] ; National Natural Science Foundation of China[U21B2038] ; National Natural Science Foundation of China[61931008] ; Hong Kong Innovation and Technology Commission [InnoHK Project the Centre for Intelligent Multidimensional Data Analysis (CIMDA)] ; Hong Kong GRF-Research Grants Council (RGC) General Research Fund[11209819 (CityU 9042816)] ; Hong Kong GRF-Research Grants Council (RGC) General Research Fund[11203820 (CityU 9042598)] ; Young Elite Scientist Sponsorship Program by the China Association for Science and Technology[2020QNRC001] ; Chinese Association for Artificial Intelligence (CAAI)-Huawei Fund
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000915825800001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/20051
专题	中国科学院计算技术研究所期刊论文
通讯作者	Lei, Jianjun
作者单位	1.Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China 2.Beijing Jiaotong Univ, Inst Informat Sci, Beijing 100044, Peoples R China 3.Beijing Key Lab Adv Informat Sci & Network Technol, Beijing 100044, Peoples R China 4.Tianjin Univ, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China 5.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 101408, Peoples R China 6.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 7.Peng Cheng Lab, Shenzhen 518055, Peoples R China 8.City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China 9.City Univ Hong Kong, Shenzhen Res Inst, Shenzhen 518057, Peoples R China
推荐引用方式 GB/T 7714	Cong, Runmin,Huang, Ke,Lei, Jianjun,et al. Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360 degrees Omnidirectional Image[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2023:13.
APA	Cong, Runmin,Huang, Ke,Lei, Jianjun,Zhao, Yao,Huang, Qingming,&Kwong, Sam.(2023).Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360 degrees Omnidirectional Image.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,13.
MLA	Cong, Runmin,et al."Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360 degrees Omnidirectional Image".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023):13.