Conference Information
BigMM 2020: International Conference on Multimedia Big Data
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New Delhi, India
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Call For Papers
Multimedia is increasingly becoming the “biggest big data” as the most important and valuable source for insights and information. It covers from everyone’s experiences to everything happening in the world. As such, multimedia big data is spurring on a tremendous amount of research and development of related technologies and applications.

The IEEE International Conference on Multimedia Big Data (BigMM), jointly sponsored by the IEEE-TCMC (Technical Committee on Multimedia Computing) and IEEE-TCSEM (Technical Committee on Semantic Computing), is a world’s premier forum of leading scholars in the highly active multimedia big data research, development and applications. The sixth BigMM conference is jointly hosted by the Jawaharlal Nehru University (JNU) and Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), will be held at School of Computer & Systems Sciences (SC&SS) in JNU, New Delhi from Septemeber 24 to 26 in 2020.

The conference aims to bring together researchers from different areas and solicits high-quality original research papers relevant in any aspect of multimedia big data but not limited to the following broad themes:

Multimedia and User Engagement

    Social media mining; affective computing
    Multimedia search; ranking; summarization
    Multimedia recommendation systems
    Security and privacy 

Multimedia Experience

    Human-computer interactions, visualization, and navigation
    Digital humanities; arts; storytelling
    Multimedia applications; multimodal interactions and interfaces

Multimedia and Big Data Content Understanding

    Multimodal integration and alignment
    Vision and language; audio/visual processing
    Large scale multimodal content (image/audio/video) understanding and processing

Multimedia Systems

    Large scale multimedia systems and middleware
    Transport and delivery
    Large scale multimedia systems and middleware
    Green computing; resource-efficient multimedia and big data computing
Last updated by Dou Sun in 2019-12-22
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