Automatic Portrait Segmentation for Image Stylization

Xiaoyong Shen1     Aaron Hertzmann2    Jiaya Jia1     Sylvain Paris2    Brian Price2    Eli Shechtman2    Ian Sachs2

1The Chinese Univeristy of Hong Kong       2Adobe Research


Our highly accurate automatic portrait segmentation method allows many portrait processing tools to be fully automatic. (a) is the input image and (b) is our automatic segmentation result. (c-e) show different automatic image stylization applications based on the segmentation result. The image is from the Flickr user “Olaf Trubel”.


Portraiture is a major art form in both photography and painting. In most instances, artists seek to make the subject stand out from its surrounding, for instance, by making it brighter or sharper. In the digital world, similar effects can be achieved by processing a portrait image with photographic or painterly filters that adapt to the semantics of the image. While many successful user-guided methods exist to delineate the subject, fully automatic techniques are lacking and yield unsatisfactory results. Our paper first addresses this problem by introducing a new automatic segmentation algorithm dedicated to portraits. We then build upon this result and describe several portrait filters that exploit our automatic segmentation algorithm to generate high-quality portraits.



This work was reoprted by Nvidia, PetaPixel, DIYPhotography, ITHome, etc.



Snapshot for paper "Automatic Portrait Segmentation for Image Stylization"
Xiaoyong Shen, Aaron Hertzmann, Jiaya Jia, Sylvain Paris, Brian Price, Eli Shechtman, Ian Sachs. Computer Graphics Forum, 35(2)(Proc. Eurographics), 2016

  [Paper (pdf, 10.97MB)]

 [Data and Code (zip, 1.5GB)] Please download from OneDrive or Baiduyun.


Last update: May. 25, 2016