Conference Information
ICMR 2022: International Conference on Multimedia Retrieval
Submission Date:
2022-01-30 Extended
Notification Date:
Conference Date:
Newark, New Jersey, USA
CCF: b   CORE: b   QUALIS: a2   Viewed: 48312   Tracked: 149   Attend: 29

Call For Papers
ACM ICMR 2022 is calling for high quality original papers addressing innovative research in multimedia retrieval and its related broad fields. The main scope of the conference is not only search and retrieval of multimedia data but also analysis and understanding of multimedia contents including community-contributed social data, lifelogging data and automatically generated sensor data, integration of diverse multimodal data, deep learning-based methodology and practical multimedia applications.

Long research papers, are up to 8 pages, plus additional pages for the list of references. These type of papers will have oral and poster presentations at the conference. Authors of the best papers will be asked to extend their work for a Special Issue in Springer’s International Journal of Multimedia Information Retrieval.

Short research papers and demonstrations are up to 4 pages, plus additional pages for the list of references. These type of papers will have only poster presentations at the conference. Papers submitted to a special session or brave new ideas track are limited to six pages per paper, plus references. Doctoral symposium papers are limited to four pages in length. Topics of Interest ICMR 2022 is a premier conference to display scientific achievements and innovative industrial products in the field of multimedia retrieval. We are seeking original high quality submissions addressing innovative research in the field. Contributions addressing the challenges of large-scale search and user behavior analysis are especially welcome.

Topics of interest include (but are not limited to):

    Multimedia content-based search and retrieval;
    Multimedia-content-based (or hybrid) recommender systems;
    Large-scale and web-scale multimedia retrieval;
    Multimedia content extraction, analysis, and indexing;
    Multimedia analytics and knowledge discovery;
    Multimedia machine learning, deep learning, and neural nets;
    Relevance feedback, active learning, and transfer learning;
    Zero-shot learning and fine-grained retrieval for multimedia;
    Event-based indexing and multimedia understanding;
    Semantic descriptors and novel high- or mid-level features;
    Crowdsourcing, community contributions, and social multimedia;
    Multimedia retrieval leveraging quality, production cues, style, framing, affect;
    Narrative generation and narrative analysis;
    User intent and human perception in multimedia retrieval;
    Query processing and relevance feedback;
    Multimedia browsing, summarization, and visualization;
    Multimedia beyond video, including 3D data and sensor data;
    Mobile multimedia browsing and search;
    Multimedia analysis/search acceleration, e.g., GPU, FPGA;
    Benchmarks and evaluation methodologies for multimedia analysis/search;
    Applications of multimedia retrieval, e.g., medicine, sports, commerce, lifelogs, travel, security, environment.
Last updated by Yi Xu in 2022-04-02
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