Image & Video Manipulation

We manipulate images and videos in order to generate new ones with different properties. We are interested in methods that maintain realistic appearance of the generated image (or video).


Relevant papers

  • R. Mechrez, I. Talmi, F. Shama, L. Zelnik-Manor, Maintaining Natural Image Statistics with the Contextual Loss, arXiv preprint arXiv:1803.04626, 13 Mar 2018. To appear in ACCV’2018. (arxiv , Project page)
  • R. Mechrez, I. Talmi, L. Zelnik-Manor, The Contextual Loss for Image Transformation with Non-Aligned Data, arXiv preprint arXiv:1803.02077, 6 Mar 2018. Oral presentation at ECCV’2018. (arxiv , Project page)
  • T. Tlusty, T. Michaeli, T. Dekel, L. Zelnik-Manor, Modifying Non-Local Variations Across Multiple Views, CVPR’2018. (arxiv, Project page)
  • R. Mechrez, E. Shechtman, L. Zelnik-Manor, Saliency Driven Image Manipulation, WACV’2018. (pdf, arxiv, Project page)
  • R. Mechrez, E. Shechtman, L. Zelnik-Manor, Photorealistic Style Transfer with Screened Poisson Equation, BMVC’2017. ( arxiv, Project page)
  • D. Rudoy and L. Zelnik-Manor, Video Inlays: A System for User-Friendly Matchmove, VRST’2013. (pdf, Project page)