Dimitrios Kollias, Queen Mary University of London, UK                                     

Stefanos Zafeiriou, Imperial College London, UK                              

Panagiotis Tzirakis,  Hume AI                                                                    

Alice Baird,  Hume AI                                                                    

Alan Cowen, Hume AI                                                 

 

Original high-quality contributions, including:

 

- databases or

- surveys and comparative studies or

- Artificial Intelligence / Machine Learning / Deep Learning / AutoML / (Data-driven or physics-based) Generative Modelling Methodologies (either Uni-Modal or Multi-Modal; Uni-Task or Multi-Task ones)

 

are solicited on the following topics:

 

i) "in-the-wild" facial expression or micro-expression analysis,

ii) "in-the-wild" facial action unit detection,

iii) "in-the-wild" valence-arousal estimation,

iv) "in-the-wild" physiological-based (e.g.,EEG, EDA) affect analysis,

v) domain adaptation for affect recognition in the previous 4 cases

vi) "in-the-wild" face recognition, detection or tracking,

vii) "in-the-wild" body recognition, detection or tracking,

viii) "in-the-wild" gesture recognition or detection,

ix) "in-the-wild" pose estimation or tracking,

x) "in-the-wild" activity recognition or tracking,

xi) "in-the-wild" lip reading and voice understanding,

xii) "in-the-wild" face and body characterization (e.g., behavioral understanding),

xiii) "in-the-wild" characteristic analysis (e.g., gait, age, gender, ethnicity recognition),

xiv) "in-the-wild" group understanding via social cues (e.g., kinship, non-blood relationships, personality) 

xv) subgroup distribution shift analysis in affect recognition

xvi) subgroup distribution shift analysis in face and body behaviour

xvii) subgroup distribution shift analysis in characteristic analysis

 

Accepted workshop papers will appear at CVPR 2023 proceedings.

Important Dates:

  Chairs: