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3D visual saliency and convolutional neural network for blind mesh quality assessment
2019
Neural computing & applications (Print)
A number of full reference and reduced reference methods have been proposed in order to estimate the perceived visual quality of 3D meshes. However, in most practical situations, there is a limited access to the information related to the reference and the distortion type. For these reasons, the development of a no-reference mesh visual quality (MVQ) approach is a critical issue, and more emphasis needs to be devoted to blind methods. In this work, we propose a noreference convolutional neural
doi:10.1007/s00521-019-04521-1
fatcat:zxk3nmtlbza5pbfyhohz7vt5zu