Perceptual-Aware Sketch Simplification Based on Integrated VGG Layers | IEEE Journals & Magazine | IEEE Xplore

Perceptual-Aware Sketch Simplification Based on Integrated VGG Layers


Abstract:

Deep learning has been recently demonstrated as an effective tool for raster-based sketch simplification. Nevertheless, it remains challenging to simplify extremely rough...Show More

Abstract:

Deep learning has been recently demonstrated as an effective tool for raster-based sketch simplification. Nevertheless, it remains challenging to simplify extremely rough sketches. We found that a simplification network trained with a simple loss, such as pixel loss or discriminator loss, may fail to retain the semantically meaningful details when simplifying a very sketchy and complicated drawing. In this paper, we show that, with a well-designed multi-layer perceptual loss, we are able to obtain aesthetic and neat simplification results preserving semantically important global structures as well as fine details without blurriness and excessive emphasis on local structures. To do so, we design a multi-layer discriminator by fusing all VGG feature layers to differentiate sketches and clean lines. The weights used in layer fusing are automatically learned via an intelligent adjustment mechanism. Furthermore, to evaluate our method, we compare our method to state-of-the-art methods through multiple experiments, including visual comparison and intensive user study.
Published in: IEEE Transactions on Visualization and Computer Graphics ( Volume: 27, Issue: 1, 01 January 2021)
Page(s): 178 - 189
Date of Publication: 24 July 2019

ISSN Information:

PubMed ID: 31352345

Funding Agency:


References

References is not available for this document.