Video Style Transfer by Adaptive Patch Sampling
This paper addresses the example-based stylization of videos. Style transfer aims at editing an image so that it matches the style of an example. This topic has recently been investigated massively, both in the industry and academia. The difficulty lies in how to capture the style of an image. For this work we build on our previous work " Split and Match " for still pictures, based on adaptive patch synthesis. We address the issue of extending that particular technique to video, ensuring that the solution is spatially and temporally consistent. Results show that our video style transfer is visually plausible, while being very competitive regarding computation time and memory when compared to neural network approaches.
