The 1st International Workshop on Human-centric Multimedia Analysis
12-16 October 2020
Seattle, United States
View on ACM MM 2020

News

  • 2020/06/15: Paper submission details is available Link
  • 2020/03/09: The website is available
  • Introduction

    The Human-centric multimedia analysis is one of the fundamental problems of multimedia understanding. It is a very challenging problem, which involves multiple tasks such as face detection and recognition, human body pattern analysis, person re-identification, human action detection, person tracking, human-object interaction, and so on. Today, multiple multimedia sensing technologies and large-scale computing infrastructures are producing at a rapid velocity a wide variety of big multi-modality data for human-centric analysis, which provide rich knowledge to help tackle these challenges. Researchers have strived to push the limits of human-centric multimedia analysis in a wide variety of applications, such as intelligent surveillance, retailing, fashion design, and services. Therefore, the purpose of this workshop is to: 1) bring together the state of the art research on human-centric multimedia analysis; 2) call for a coordinated effort to understand the opportunities and challenges emerging in human-centric multimedia analysis; 3) identify key tasks and evaluate the state-of-the-art methods; 4) showcase innovative methodologies and ideas; 5) introduce interesting real-world human-centric multimedia analysis systems or applications; and 6) propose new real-world datasets and discuss future directions. We solicit original contributions in all fields of human-centric multimedia analysis that explore the multi-modality data to help us understand the heavier of humans and promote the multimodal human-machine interaction. We believe the workshop will offer a timely collection of research updates to benefit the researchers and practitioners working in the broad multimedia communities. To this end, we solicit original research and survey papers in (but not limited to) the following topics:

    • Face detection, recognition, face anti-spoofing, face landmark detection and parsing.
    • Human detection, pose estimation, human parsing, and pose tracking.
    • Human 3D shape estimation and reconstruction.
    • Human gait recognition, person re-identification and person tracking.
    • Human action recognition and detection
    • Human activity recognition using non-visual sensors
    • Huma-computer interaction / Human object interaction
    • Multimedia event detection
    • Anomaly event detection
    • Human crowd analysis


    Important Date

    • Workshop paper submission: July 30
    • Workshop paper notifications: August 26
    • Workshop camera-ready paper: September 2

    Submission Page

    Submissions are made via Link. Please select the track of The 1st International Workshop on Human-centric Multimedia Analysis

    Paper Format

    Submitted papers (.pdf format) must use the ACM Article Template. Please remember to add Concepts and Keywords Link

    Length

    The HuMA workshop will welcome two kinds of submissions:

    • Research papers which can be 6 to 8 pages. Up to two additional pages may be added for references. The reference pages must only contain references. Optionally, you may upload supplementary material that complements your submission (100Mb limit).
    • Demo papers which can be 2 pages.

    More submission details: Link

    Reviewing Process

    The full paper submission deadline will be around July 30, and the decisions will be out on August 26. Paper submissions must conform with the “double-blind” review policy. All papers will be peer-reviewed by experts in the field, they will receive at least three reviews. Acceptance will be based on relevance to the workshop, scientific novelty, and technical quality. The workshop papers will be published in the ACM Digital Library.

    Tentative Programs

    • To Be Announced

    Organizers

    Wu Liu

    JD AI Research, Beijing, China

    Chuang Gan

    MIT-IBM Watson AI Lab

    Jingkuan Song

    University of Electronic Science and Technology of China

    Dingwen Zhang

    Xidian University

    Wenbing Huang

    Tsinghua University

    John Smith

    IBM Research

    More information