[Face-research-list] Call for papers - Workshop on Human Behavior Understanding (HBU) @WACV 2021

******************************************************************** CALL FOR PAPERS - HBU 2021 11th International Workshop on Human Behavior Understanding (HBU) Focus theme: Multi-source aspects of behavioral understanding Held in conjunction with WACV 2021 https://lmi.fe.uni-lj.si/hbu2021 Paper submission deadline: November 2nd, 2020 Notifications: November 18th, 2020 ********************************************************************* ORGANIZERS Abhijit Das, Indian Statistical Institute, Kolkata, India Qiang Ji, Rensselaer Polytechnic Institute, United States Umapada Pal, Indian Statistical Institute, Kolkata, India Albert Ali Salah, Utrecht University, The Netherlands Vitomir Štruc, University of Ljubljana, Slovenia ABOUT Domains for human behaviour understanding predominantly (e.g., multimedia, human-computer interaction, robotics, affective computing and social signal processing) rely on advanced pattern recognition techniques to automatically interpret complex behavioural patterns generated when humans interact with machines or with other agents. This is a challenging research area where many issues are still open, including the joint modelling of behavioural cues taking place at different time scales, the inherent uncertainty of machine detectable evidence of human behaviour, the mutual influence of people involved in interactions, the presence of long term dependencies in observations extracted from human behaviour, and the important role of dynamics in human behaviour understanding. Computer vision is a key technology for analysis and synthesis of human behaviour but stands to gain much from multi-modality and multi-source processing, in terms of improving accuracy, resource use, robustness, and contextualization. This workshop, organized as part of WACV 2021, will gather researchers dealing with the problem of modelling human behaviour under its multiple facets (expression of emotions, display of relational attitudes, the performance of an individual or joint actions, etc.), with particular attention to multi-source aspects, including multi-sensor, multi-participant and multi-modal settings. Example challenges are the additional resource and robustness constraints, explorations in information fusion, social and contextual aspects of interactions, and building multi-source representations of social and affective signals with the goal of advancing the state-of-the-art. The HBU workshops, previously organized as satellite events to major conferences in different disciplines such as ICPR’10, AMI’11, IROS’12, ACMMM’13, ECCV’14, UBICOMP’15, ACMMM’16, FG’18, ECCV’18, ICCV’19 have a unique aspect of fostering cross-pollination of disciplines, bringing together researchers from a variety of fields, such as computer vision, HCI, artificial intelligence, pattern recognition, interaction design, ambient intelligence, psychology and robotics. The diversity of human behaviour, the richness of multimodal data that arises from its analysis, and the multitude of applications that demand rapid progress in this area ensure that the HBU Workshops provide a timely and relevant discussion and dissemination platform. For HBU@WACV, we particularly solicit contributions on human behaviour understanding that combine multiple sources of information, be it across modalities, sensors, or subjects under observation. The workshop solicits papers on general topics related to human behaviour understanding, but with a distinct focus on multi-source solutions. TOPICS OF INTEREST Topics of interest include, but are not limited to: + Multimodal solutions for human behaviour modelling and analysis + Multimodal solutions towards behavioural biometrics (gait, handwriting, keystroke dynamics, etc.) + Methods for multi-instance learning in behavioural understanding, + Analysis of multi-participant settings and of social interactions, + Multi-instance representation for characterizing human health, empathy, + Deep learning for multi-party interactions + Multimodal deep learning for behaviour understanding + Adversarial learning approaches + Related sensor technologies + Information fusions approach for behaviour analysis + Realistic behaviour synthesis in multiple modalities and for multi-party settings + Mobile and wearable systems for behaviour monitoring + Datasets and benchmarks + Related applications PAPER SUBMISSION Submission instruction can be found at https://lmi.fe.uni-lj.si/hbu2021/paper-submission/ Please feel free to contact for any further details. Abhijit Das, Qiang Ji, Umapada Pal, Albert Ali Salah, Vitomir Štruc HBU 2021 Organizers