Human face is probably the most researched object in image analysis and computer vision. One of the main reasons behind its popularity is that the applications of automatic face analysis algorithms are numerous and span several fields, from Human Computer Interaction (expression recognition for automatic analysis of affect) to law enforcement (face recognition). Until less than a decade ago the majority of face analysis algorithms have been evaluated in databases that were captured in constrained conditions. The research has gradually shifted to facial images captured “in-the-wild”. For certain tasks, mostly revolving around analysis of facial affect, such as estimation of continuous emotion dimensions, as well as detection of activation of FAUs, research results are still mainly reported in datasets that contain facial images of a small number of people captured in laboratory conditions. In CVPR 2016, we organise a workshop on affect "in-the-wild" (Affect-W). The workshop solicits papers on databases, benchmarks and original technical contributions on vision based affect analysis in unconstrained conditions.
Programme committee:
Ioannis Patras,
Queen Mary University, UK
Ioannis Marras,
Queen Mary University London, UK
Qiang Ji,
Rensselaer Polytechnic Institute, USA
Michel Valstar,
University of Nottingham, UK
Louis-Philippe Morency,
Carnegie Mellon University, USA
Ognjen Rudovic,
Imperial College London, UK
Nicu Sebe,
University of Trento, IT
Ioannis Panagakis,
Imperial College, UK
Anastasios Roussos,
Imperial College, UK
Lijun Yin,
Binghamton University, USA
Akshay Asthana,
Seeing Machines, Australia
Papers should adhere to the same formatting guidelines as the main CVPR 2016 conference. The review process will be double blind. For important dates, please see below.