No-reference synthetic image quality assessment with convolutional neural network and local image saliency-Reference-Cited by-同舟云学术

No-reference synthetic image quality assessment with convolutional neural network and local image saliency

Published:2019-03-30 Issue:2 Volume:5 Page:193-208
ISSN:2096-0433
Container-title:Computational Visual Media
language:en
Short-container-title:Comp. Visual Media

Author:

Wang Xiaochuan,Liang Xiaohui,Yang Bailin,Li Frederick W. B.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition

Link

http://link.springer.com/content/pdf/10.1007/s41095-019-0131-6.pdf

Reference45 articles.

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2. Smolic, A. 3D video and free viewpoint video: From capture to display. Pattern Recognition Vol. 44, No. 9, 1958–1968, 2011.

3. Smolic, A.; Mueller, K.; Merkle, P.; Kauff, P.; Wiegand, T. An overview of available and emerging 3D video formats and depth enhanced stereo as efficient generic solution. In: Proceedings of the Picture Coding Symposium, 1–4, 2009.

4. Wang, X.; Liang, X.; Yang, B.; Li, F. W. Scalable remote rendering using synthesized image quality assessment. IEEE Access Vol. 6, 36595–36610, 2018.

5. Mark, W. Post-rendering 3D image warping: Visibility, reconstruction, and performance for depth-image warping. Technical Report. Chapel Hill, NC, USA, 1999.

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