Maintaining Internal Image Statistics in Synthesized Images
Lihi Zelnik-Manor
(Technion, Israel)
Abstract:
Recent work has shown impressive success in automatically synthesizing new
images with desired properties such as transferring painterly style, modifying
facial expressions, increasing image resolution or manipulating the center of
attention of the image. In this talk I will discuss two of the standing
challenges in image synthesis and how we tackle them: - I will describe our
efforts in making the synthesized images more photo-realistic. - I will
further show how we can broaden the scope of data that can be used for
training synthesis networks, and with that provide a solution to new
applications.