Deep Audio-Visual Learning: A Survey

doi:10.1007/s11633-021-1293-0

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	Deep Audio-Visual Learning: A Survey
	Hao Zhu 1,2; Man-Di Luo2,3 ; Rui Wang1,2 ; Ai-Hua Zheng 1; Ran He2,3,4
发表期刊	International Journal of Automation and Computing
ISSN	1476-8186
	2021
卷号	18 期号:3 页码:351-376
摘要	Audio-visual learning, aimed at exploiting the relationship between audio and visual modalities, has drawn considerable attention since deep learning started to be used successfully. Researchers tend to leverage these two modalities to improve the performance of previously considered single-modality tasks or address new challenging problems. In this paper, we provide a comprehensive survey of recent audio-visual learning development. We divide the current audio-visual learning tasks into four different subfields: audio-visual separation and localization, audio-visual correspondence learning, audio-visual generation, and audio-visual representation learning. State-of-the-art methods, as well as the remaining challenges of each subfield, are further discussed. Finally, we summarize the commonly used datasets and challenges.
关键词	Deep audio-visual learning audio-visual separation and localization correspondence learning generative models representation learning
DOI	10.1007/s11633-021-1293-0
引用统计	被引频次：64[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44288
专题	学术期刊_Machine Intelligence Research 投资企业
作者单位	1.Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei 230601, China 2.Center for Research on Intelligent Perception and Computing (CRIPAC) and National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 3.School of Artificial Intelligence, University of the Chinese Academy of Sciences, Beijing 100049, China 4.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Hao Zhu,Man-Di Luo,Rui Wang,et al. Deep Audio-Visual Learning: A Survey[J]. International Journal of Automation and Computing,2021,18(3):351-376.
APA	Hao Zhu,Man-Di Luo,Rui Wang,Ai-Hua Zheng,&Ran He.(2021).Deep Audio-Visual Learning: A Survey.International Journal of Automation and Computing,18(3),351-376.
MLA	Hao Zhu,et al."Deep Audio-Visual Learning: A Survey".International Journal of Automation and Computing 18.3(2021):351-376.

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