DeepWarp: Photorealistic Image Resynthesis for Gaze Manipulation

Understand

In this work, we consider the task of generating highly-realistic images of a given face with a redirected gaze.

• We treat this problem as a specific instance of conditional image generation and suggest a new deep architecture that can handle this task very well as revealed by numerical comparison with prior art and a user study.
• Our deep architecture performs coarse-to-fine warping with an additional intensity correction of individual pixels.
• All these operations are performed in a feed-forward manner, and the parameters associated with different operations are learned jointly in the end-to-end fashion.