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Computer Vision and Image Analysis of Art 2021

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Kurt Heumiller, David G. Stork:
Computer Vision and Image Analysis of Art 2021, online, January 11-28, 2021. Society for Imaging Science and Technology 2021

Articles

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CVAA Conference Overview and Papers Program. 1-5
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  - conf/ei-cvaa/PadhyeMF21
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Snehal A. Padhye, David Messinger, James A. Ferwerda:
A Web-based Visualization Tool for Multispectral Images. 1-6
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  - conf/ei-cvaa/StorkBCG21
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David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths:
Computational identification of significant actors in paintings through symbols and attributes. 1-8
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George H. Cann, Anthony Bourached, Ryan-Rhys Griffiths, David G. Stork:
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. 1-8
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  - conf/ei-cvaa/BanarSGDK21
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Nikolay Banar, Matthia Sabatelli, Pierre Geurts, Walter Daelemans, Mike Kestemont:
Transfer Learning with Style Transfer between the Photorealistic and Artistic Domain. 1-9
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Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths, David G. Stork:
Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars. 1-10
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David G. Stork, Christopher W. Tyler, Sara J. Schechner:
Did Tim Paint a Vermeer? 1-12
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Yuchun Yan, Hayan Choi, Hyeon-Jeong Suk:
Exploring the Facial Color Representative Regions Using the Humanae Images. 1-7

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