Computational Visual Media

ISSN: 2096-0433 (Print) 2096-0662 (Online)

Description

Computational Visual Media is a peer-reviewed open access journal published quarterly by Tsinghua University Press and Springer under the SpringerOpen brand. It publishes original high-quality research papers and significant review articles on novel ideas, methods, and systems relevant to visual media.

The journal publishes articles that focus on, but are not limited to, the following areas:

•  3D visual media processing
•  Classification and composition of visual media
•  Cognition of visual media
•  Content security for visual media
•  Enhancement and re-rendering of visual media
•  Geometric computing for images and video
•  Interactive editing of visual media
•  Machine learning for visual media
•  Social media computing
•  Understanding of visual media
•  Visual media retrieval
•  Visualization and visual analytics

Other interdisciplinary research into visual media that combines aspects of computer graphics, computer vision, image and video processing, geometric computing, and machine learning is also within the journal's scope.

The publication costs are covered by Tsinghua University so authors do not need to pay an article-processing charge.

Computational Visual Media operates a double-blind peer-review system, where the reviewers do not know the names or affiliations of the authors and the reviewer reports provided to the authors are anonymous.

All articles published are made freely and permanently accessible online immediately upon publication, without subscription charges or registration barriers. Further information about open access can be found at https://www.springeropen.com/about/open-access.

As authors of articles published in Computational Visual Media  you are the copyright holders of your article and have granted to any third party, in advance and in perpetuity, the right to use, reproduce or disseminate your article, according to the SpringerOpen copyright and license agreement (https://www.springeropen.com/get-published/copyright/copyright-and-license-agreement).

For those of you who are US government employees or are prevented from being copyright holders for similar reasons, SpringerOpen can accommodate non-standard copyright lines. Please contact info@springeropen.com if further information is needed.

 

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