yichang

We are looking at gain maps to see if we can reduce the artifacts. Styles with hard shadow are more challenging. eg Olaf Blecker http://i1.dripimg.com/t/460000/6554/96/450324_500_8a28bd.jpg (Note that high contrast doesn't mean hard shadow)

Both papers use multi-scale approach to capture textures in different scales. While Bae's work is global transfer, this paper uses local transfer. This paper first uses a technique called "sift flow" in computer vision to compute the correspondences between example face and input face, and then transfer the image statistics locally, based on the correspondences.

I'm planning to release some demo code before the presentation at August :-)

Exactly. In my viewpoint, the dense correspondence is another key factor that makes this technique work.

The main difference of this method is doing the transfer locally - while most off-the-shelf filters only create global effects.