Since the end of 2019, the whole world has been living with the effects of the COVID-19 disease. Due to the airborne nature of the novel coronavirus, the COVID-19 disease has spread rapidly in many countries in a short time and has also been declared a global pandemic. Several preventive measures were implemented to reduce the spread of this disease, including social distancing, wearing face masks, avoiding large crowds, and others.

To help monitor public behavior and compliance with the implemented prevention measures, to gather reliable data for epidemiological models, facilitate authorized access and authentication, ensure safety and security despite the COVID-19 pandemic, it is critical to develop automated machine learning and computer vision based techniques that can help with these tasks. The COVID-19 pandemic has initiated research and development of computer-aided systems that can be used to prevent and monitor not only COVID-19 but also similar diseases that may appear in the future.

The goal of this workshop is to present the most recent and advanced work related to face and gesture analysis in the scope of COVID-19. We are interested in all COVID-19 related studies that focus on the detection of face mask, subjects' behaviors in public areas, analysis of pandemic and preventions-related real-world face and gesture data, prevention control and monitoring systems for unconstrained real-world conditions and related problems.

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

• Face mask detection,
• Masked face detection and recognition,
• Face-hand interaction detection,
• COVID-19 monitoring and control systems related to face and gesture analysis,
• Social distance tracking and control systems,
• Dataset bias analysis on COVID-19 datasets (face mask, face-hand, social distance,...),
• Face, gesture and body analysis for monitoring intervention-measure compliance,
• Behavior understanding relevant for COVID-19,
• Analysis of social interactions relevant to COVID-19,
• Soft-biometric analysis on masked faces (age, gender, ...),
• Generative models relevant in the scope of COVID-19,
• Novel datasets and performance benchmarks,
• Related applications.

Paper submission:

Authors should follow the official FG 2021 paper formatting instructions available from FG 2021. Note that FG4COVID19 does not have a short-paper category, so all submissions should be up to 8 pages including references. Paper submission should be done through the CMT System: CMT Submission.

All accepted papers will be published in the official proceedings of the »16th International Conference on Automatic Face and Gesture Recognition (FG 2021)« and send for inclusion into IEEE Xplore.

The workshop has two rounds of submission. The authors are free to submit in either the first or the second round.

Selected papers from the first submission round will be invited to submit extended versions of their work to a special issue organized in the Image and Vision Computing journal.

Deadlines:

• First round submission deadline: 31 July 2021, 11:59pm PST (UPDATED)
• Second round sumission deadline: 28 September 2021, 11:59pm PST 17 October 2021, 11:59pm PST (UPDATED)