When
28. January.Time: 15:00 - 16:00
What
Abstract of the talk
Until recently, the generation of images in computers was mainly done via
algorithms that leverage mathematical rules of physical laws, i.e., are
relatively simple to implement. What remained problematic for a long period of
time was the generation of images that closely resemble hand-drawn artwork.
The critical issue is that unique artistic style is typically hard to describe
by a set of mathematical rules. Nowadays, in the age of artificial intelligence
where cars are nearly autonomous, and computers can defeat us in chess or Go,
one could expect AI to generate art indistinguishable from canvases of famous
painters. Surprisingly, the first approach that passed the artistic version of
the Turing Test was not based on neural networks. In this talk, we discuss why
that happened, the current capabilities of neural techniques, and how they can
help artists produce unique artistic content automatically in near future.
Bio
Daniel Sýkora is a Professor at the Department of Computer Graphics and
Interaction, Faculty of Electrical Engineering, Czech Technical University in
Prague, where he leads a research group focused on developing algorithms for
artists. Their goal is to empower creative freedom by employing traditional
techniques while reducing the repetitiveness of manual work. Daniel and his
team collaborate with renowned industrial partners and professional studios
to integrate algorithms they develop into production pipelines. For his
contribution to the field of computer-assisted production of artistic content
Daniel received numerous awards including The Neuron Award for Promising Young
Scientists, Best in Show Award at SIGGRAPH, or Günter Enderle Best Paper Award
at Eurographics.