FML: Face Model Learning from Videos

Monocular image-based 3D reconstruction of faces is a long-standing problem in computer vision. Since image data is a 2D projection of a 3D face, the resulting depth ambiguity makes the problem ill-posed. Most existing methods rely on data-driven priors that are built from limited 3D face scans. In contrast, we propose multi-frame video-based self-supervised training of a deep network that (i) learns a face identity model both in shape and appearance while (ii) jointly learning to reconstruct 3D faces. Our face model is learned using only corpora of in-the-wild video clips collected from the Internet. This virtually endless source of training data enables learning of a highly general 3D face model. In order to achieve this, we propose a novel multi-frame consistency loss that ensures consistent shape and appearance across multiple frames of a subject's face, thus minimizing depth ambiguity. At test time we can use an arbitrary number of frames, so that we can perform both monocular as well as multi-frame reconstruction.Comment: CVPR 2019 (Oral). Video: https://www.youtube.com/watch?v=SG2BwxCw0lQ, Project Page: https://gvv.mpi-inf.mpg.de/projects/FML19

Homo Virtualis: existence in Internet space

The study of a person existence in Internet space is certainly an actual task, since the Internet is not only a source of innovation, but also the cause of society's transformations and the social and cultural problems that arise in connection with this. Computer network is global. It is used by people of different professions, age, level and nature of education, living around the world and belonging to different cultures. It complicates the problem of developing common standards of behavior, a system of norms and rules that could be widely accepted by all users. On the other hand, the Internet space can be viewed as a new form of existence where physical laws do not work, and in connection with this, social ones are often questioned. This paper focuses on how social norms regulate relations in Internet space. The authors represents the typology of deviant behavior in the network. The empirical basis of the research includes the sociological survey of students of the senior courses in the Institute of Computer Science and Technology of Peter the Great St. Petersburg Polytechnic University. Sociological survey allows to identify students’ understanding of Internet space. The selection of students is conditioned by the fact that IT professionals are considered simultaneously as ordinary users of the network and as future professionals in this field