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Cited by 170

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Automatic Portrait Segmentation for Image Stylization

Shen, Xiaoyong, Hertzmann, Aaron, Jia, Jiaya, Paris, Sylvain, Price, Brian, Shechtman, Eli, Sachs, Ian·2016·Computer Graphics Forum

Abstract

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.

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Metadata

Authors
Shen, X., Hertzmann, A., Jia, J., Paris, S., Price, B., Shechtman, E., & Sachs, I.
Venue
Computer Graphics Forum
Publisher
Wiley
Published
2016-05
Volume
35
Issue
2
Pages
93-102
ISSN
  • 0167-7055 (ISSN-L)
  • 1467-8659
OpenAlex
W2400000673
Cited by
170
References
4
FWCI
15.29
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Automatic Portrait Segmentation for Image Stylization. https://app.cochat.ai/papers/10.1111/cgf.12814
The paper
Shen, X., Hertzmann, A., Jia, J., Paris, S., Price, B., Shechtman, E., & Sachs, I. (2016). Automatic Portrait Segmentation for Image Stylization. Computer Graphics Forum. https://doi.org/10.1111/cgf.12814

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.