Keynote Speakers

Stefanos Zafeiriou, Imperial College London - Estimating Affect in-the-wild

The last twenty years a lot of research has been conducted on developing automatic human behavior analysis techniques using data captured in well-controlled conditions and, usually, under a strict scenario in mind. In real world conditions and in unscripted real life situations human behavior is much more complex. To this end we recently made a considerable effort to collect and annotate unscripted spontaneous facial behavior in arbitrary recording conditions. Using the collected database, which we coin Aff-Wild, we organized the first challenge on affect analysis in-the-wild. In this talk, I will present the Aff-Wild benchmark. I will also outline some of the methodologies presented in the challenge. Furthermore, I will describe some of the methods that we have recently proposed, based on deep neural networks, which achieve state-of-the-art performance in Aff-Wild benchmark. I will also demonstrate how this baseline we developed can be used to push the state-of-the-art in standard benchmarks, as well.

Michael Black, Max Planck Institute - Learning to be a Digital Human

We interact with the world through our bodies. As many of our interactions move on-line, we become literally disembodied in the virtual world, breaking the metaphor of the Internet as a replica of our physical space. Can we take our bodies with us on-line? Can we create virtual humans the look and behave in ways that are indistinguishable from real people? This talk will introduce the current state of the art in capturing, modeling, and animating realistic 3D human bodies. The talk will introduce the latest technology for 4-dimensional body capture and the use of machine learning to create avatars that mimic our shape and motion. We then exploit these detailed models of human bodies and how they move, to train deep neural networks to estimate 3D human shape and pose from images and videos.

Bios

Stefanos Zafeiriou is currently a Reader in Machine Learning and Computer Vision with the Department of Computing, Imperial College London, London, U.K, and a Distinguishing Research Fellow with University of Oulu under Finish Distinguishing Professor Programme. He was a recipient of the Prestigious Junior Research Fellowships from Imperial College London in 2011 to start his own independent research group. He was the recipient of the President's Medal for Excellence in Research Supervision for 2016. He has co-authored over 55 journal papers mainly on novel statistical machine learning methodologies applied to computer vision problems, such as 2-D/3-D face analysis, deformable object fitting and tracking, shape from shading, and human behaviour analysis, published in the most prestigious journals in his field of research, such as the IEEE T-PAMI, the International Journal of Computer Vision, the IEEE T-IP, the IEEE T-NNLS, the IEEE T-VCG, and the IEEE T-IFS, and many papers in top conferences, such as CVPR, ICCV, ECCV, ICML. His students are frequent recipients of very prestigious and highly competitive fellowships, such as the Google Fellowship x2, the Intel Fellowship, and the Qualcomm Fellowship x3. He is the General Chair of BMVC 2017.

Michael Black received his B.Sc. from the University of British Columbia (1985), his M.S. from Stanford (1989), and his Ph.D. from Yale University (1992). After post-doctoral research at the University of Toronto, he worked at Xerox PARC as a member of research staff and an area manager. From 2000 to 2010 he was on the faculty of Brown University in the Department of Computer Science (Assoc. Prof. 2000-2004, Prof. 2004-2010). He is one of the founding directors at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department. He is also a Distinguished Amazon Scholar, an Honorarprofessor at the University of Tuebingen, and Adjunct Professor at Brown University. His work has won several awards including the IEEE Computer Society Outstanding Paper Award (1991), Honorable Mention for the Marr Prize (1999 and 2005), the 2010 Koenderink Prize for Fundamental Contributions in Computer Vision, and the 2013 Helmholtz Prize for work that has stood the test of time. He is a foreign member of the Royal Swedish Academy of Sciences. In 2013 he co-founded Body Labs Inc., which was acquired by Amazon in 2017.