IEEE 4th International Conference on Multimedia Information Processing and Retrieval (IEEE MIPR 2021)

March 22-24, 2021. Tokyo, Japan.

Special Session: Knowledge-Driven Multi-modal Deep Analysis for Multimedia

With the rapid development of Internet and multimedia services in the past decade, a huge amount of user-generated and service provider-generated multimedia data become available. These data are heterogeneous and multi-modal in nature, imposing great challenges for processing and analyzing them. Multi-modal data consist of a mixture of various types of data from different modalities such as texts, images, videos, audios etc. Data-driven correlational representation and knowledge-guided fusion are the main scientific problems for multimedia analysis. In order to gather and present innovative research on the following aspects: 1) multi-modal correlational representation: multi-modal fusion of data across different modalities, and 2) multi-modal data and knowledge fusion: multi-modal fusion of data with domain knowledge, we solicit submissions of high-quality manuscripts reporting the state-of-the-art techniques and trends in this field.

List of Topics

  • Multi-modal representation learning with knowledge
  • Multi-modal data fusion with knowledge
  • Knowledge representation for multi-modal data
  • Deep cross-modality alignment with knowledge
  • Methodology and architectures to improve model explainability with knowledge
  • Multi-modal deep analysis for innovative multimedia applications, such as person reidentification, social network analysis, cross-modal retrieval, recommendation systems and so on.

Important Dates

  • Paper Submission Deadline: November 20, 2020
  • Notification of Acceptance: December 25, 2020
  • Camera-Ready Deadline: January 8, 2021

Paper Submission Instructions

Special session paper manuscripts must be in English of up to 6 pages excluding references (using the IEEE two-column template instructions). Submissions should include the title, author(s), affiliation(s), e-mail address(es), abstract, and postal address(es) on the first page. The templates in Word or LaTex format are available here. To submit your papers to this session, please select the “Special Session: Knowledge-Driven Multi-modal Deep Analysis for Multimedia” in Microsoft CMT submission site.

Special Session Organizers