Publications

Semantic Soft Segmentation

Publication

ACM SIGGRAPH 2018, 2018

Authors

Yagiz Aksoy, Tae-Hyun Oh, Sylvain Paris, Marc Pollefeys, Wojciech Matusik

Abstract

Accurate representation of soft transitions between image regions is essential for high-quality image editing and compositing. Current techniques for generating such representations depend heavily on interaction by a skilled visual artist, as creating such accurate object selections is a tedious task. In this work, we introduce semantic soft segments, a set of layers that correspond to semantically meaningful regions in an image with accurate soft transitions between different objects. We approach this problem from a spectral segmentation angle and propose a graph structure that embeds texture and color features from the image as well as higher-level semantic information generated by a neural network. The soft segments are generated via eigendecomposition of the carefully constructed Laplacian matrix fully automatically. We demonstrate that otherwise complex image editing tasks can be done with little effort using semantic soft segments.

Paper

sss_3.pdf

Project Website

http://people.inf.ethz.ch/aksoyy/sss/

CDFG

© 2020 The Computational Design & Fabrication Group