NeuralGiga: Neural Giga-Image Representation with Anti-Aliasing and Continuous Viewing

doi:10.1109/IECON51785.2023.10312348

	NeuralGiga: Neural Giga-Image Representation with Anti-Aliasing and Continuous Viewing
	Luo, Xi1,2,3 ; Li, Yuwei1,2,3 ; Wu, Minye 4; Ma, Yuexin1 ; Xu, Lan1 ; Yu, Jingyi1
	2023-10-19
会议录名称	IECON 2023- 49TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
ISSN	1553-572X
发表状态	已发表
DOI	10.1109/IECON51785.2023.10312348
摘要	A gigapixel image consists of billions of pixels with color information to record fine details of the scene, leading to tremendous data overload for storage and display. Recent advances of gigapixel imaging still suffer from large storage size, I/O overhead or spatial aliasing for achieving real-time rendering especially during zoom-in or zoom-out. To fill this gap, in this paper, we propose NeuralGiga, a novel neural representation of gigapixel images with an effective neural rendering scheme. NeuralGiga implicitly encodes the entire image into a light-weight network which maps pixel coordinates into RGB values with efficient storage overload. In our novel neural rendering network, to enable high-quality giga-image regression with anti-aliasing and continuous viewing effect, we introduce a Spectrum Multi-Layer Perceptron (MLP) design and a Gaussian-based Integrated Random Fourier Feature Mapping (GIRFFM) scheme. Extensive experiments on various scenarios illustrate the effectiveness of our approach to achieve high-quality neural giga-image representation for both storage and display. © 2023 IEEE.
关键词	Image Processing
会议名称	49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
会议地点	Singapore, Singapore
会议日期	16-19 Oct. 2023
URL	查看原文
收录类别	EI
语种	英语
出版者	IEEE Computer Society
EI入藏号	20235015211740
EI主题词	Pixels
EISSN	2577-1647
EI分类号	722.1 Data Storage, Equipment and Techniques ; 723.2 Data Processing and Image Processing ; 723.4 Artificial Intelligence ; 723.5 Computer Applications
原始文献类型	Conference article (CA)
来源库	IEEE
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/347927
专题	信息科学与技术学院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_博士生信息科学与技术学院_PI研究组_许岚组信息科学与技术学院_PI研究组_马月昕
作者单位	1.School of Information Science and Technology, ShanghaiTech University, China; 2.University of Chinese Academy of Sciences, China; 3.Shanghai Institute of Microsystem and Information Technology, China; 4.Ku Leuven, Belgium
第一作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Luo, Xi,Li, Yuwei,Wu, Minye,et al. NeuralGiga: Neural Giga-Image Representation with Anti-Aliasing and Continuous Viewing[C]:IEEE Computer Society,2023.