Maintaining Internal Image Statistics in Synthesized Images

Lihi Zelnik-Manor (Technion, Israel)


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.