Over the past few years, there have been fundamental breakthroughs in core problems in machine learning, largely driven by advances in deep neural networks. The amount of annotated data drastically increased and supervised deep discriminative models exceed ...
A large body of research has focused on adversarial attacks which require to modify all input features with small l2- or l∞-norms. In this paper we instead focus on query-efficient sparse attacks in the black-box setting. Our versatile framework, Sparse-RS ...
Makeup is a simple and easy instrument that can alter the appearance of a person’s face, and hence, create a presentation attack on face recognition (FR) systems. These attacks, especially the ones mimicking ageing, are difficult to detect due to their clo ...
Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...
Recovering a person's height from a single image is important for virtual garment fitting, autonomous driving and surveillance. However, it is also very challenging without absolute scale information. Here, we examine the rarely addressed case, where camer ...
A large part of computer vision research is devoted to building models
and algorithms aimed at understanding human appearance and behaviour
from images and videos. Ultimately, we want to build automated systems
that are at least as capable as people when i ...
