CASIA OpenIR  > 模式识别国家重点实验室  > 先进数据分析与学习
Deep generative video prediction
Yu, Tingzhao1,2; Wang, Lingfeng1,3; Gu, Huxiang1; Xiang, Shiming1; Pan, Chunhong1
Source PublicationPATTERN RECOGNITION LETTERS
2018-07-15
Volume110Pages:58-65
SubtypeArticle
AbstractVideo prediction plays a fundamental role in video analysis and pattern recognition. However, the generated future frames are often blurred, which are not sufficient for further research. To overcome this obstacle, this paper proposes a new deep generative video prediction network under the framework of generative adversarial nets. The network consists of three components: a motion encoder, a frame generator and a frame discriminator. The motion encoder receives multiple frame differences (also known as Eulenan motion) as input and outputs a global video motion representation. The frame generator is a pseudo-reverse two-stream network to generate the future frame. The frame discriminator is a discriminative 3D convolution network to determine whether the given frame is derived from the true future frame distribution or not. The frame generator and frame discriminator train jointly in an adversarial manner until a Nash equilibrium. Motivated by theories on color filter array, this paper also designs a novel cross channel color gradient (3CG) loss as a guidance of deblurring. Experiments on two state-of-the-art data sets demonstrate that the proposed network is promising. (C) 2018 Elsevier B.V. All rights reserved.
KeywordVideo Prediction Two Stream Adversarial Training Convlstm
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.patrec.2018.03.027
WOS KeywordSURVEILLANCE
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61403376 ; Beijing Natural Science Foundation(4162064) ; Open Research Fund of Hunan Provincial Key Laboratory of Network Investigational Technology(2015HNWLFZ055) ; 61573352 ; 91646207 ; 91438105)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000434780700009
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/22054
Collection模式识别国家重点实验室_先进数据分析与学习
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 101408, Peoples R China
3.Hunan Police Acad, Hunan Prov Key Lab Network Invest Technol, Changsha 410138, Hunan, Peoples R China
Recommended Citation
GB/T 7714
Yu, Tingzhao,Wang, Lingfeng,Gu, Huxiang,et al. Deep generative video prediction[J]. PATTERN RECOGNITION LETTERS,2018,110:58-65.
APA Yu, Tingzhao,Wang, Lingfeng,Gu, Huxiang,Xiang, Shiming,&Pan, Chunhong.(2018).Deep generative video prediction.PATTERN RECOGNITION LETTERS,110,58-65.
MLA Yu, Tingzhao,et al."Deep generative video prediction".PATTERN RECOGNITION LETTERS 110(2018):58-65.
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