Perceptually inspired real-time artistic style transfer for video stream

This study presents a real-time texture transfer method for artistic style transfer for video stream. We propose a parallel framework using a T-shaped kernel to enhance the computational performance. With regard to accelerated motion estimation, which is necessarily required for maintaining temporal coherence, we present a method using a downscaled motion field to successfully achieve high real-time performance for texture transfer of video stream. In addition, to enhance the artistic quality, we calculate the level of abstraction using visual saliency and integrate it with the texture transfer algorithm. Thus, our algorithm can stylize video with perceptual enhancements.

Duke Scholars

Author Feng Tian DKU Faculty