The 3rd International Workshop on Human-centric Multimedia Analysis
10-14 October 2022
Lisbon, Portugal
View on ACM MM 2022

News

2022/05/05: The website is available

Introduction

Human-centric multimedia analysis is one of the fundamental problems in multimedia understanding. It is a very challenging problem that involves multiple tasks such as face detection and recognition, human pose estimation, human action detection, human-object interaction, person tracking, person re-identification, and so on. Today, ubiquitous multimedia sensors and large-scale computing infrastructures are producing at a rapid velocity a wide variety of big multi-modality data for human-centric analysis, which provides rich knowledge to tackle these challenges. Researchers have strived to push the limits of human-centric multimedia analysis in various 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 understand the behavior of humans. We believe this workshop will offer a timely collection of research updates to benefit researchers and practitioners 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
  • Human-computer interaction / Human object interaction
  • Multimedia event detection
  • Anomaly event detection
  • Human crowd analysis


Keynote Speakers

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Organizers

Dingwen Zhang

Northwestern Polytechnical University, Xi’an, China

Chaowei Fang

Xidian University, Xi’an, China

Wu Liu

JD AI Research, Beijing, China

Xinchen Liu

JD AI Research, Beijing, China

Jingkuan Song

University of Electronic Science and Technology of China

Hongyuan Zhu

Agency for Science, Technology, and Research (A*STAR), Singapore

Wenbing Huang

Tsinghua University

John Smith

IBM Research

If you have any questions, feel free to contact chaoweifang [at] outlook [dot] com

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