In this paper, we propose an objective quality metric to evaluate the perceived visual quality
of 3D meshes. Our method relies on pre-trained convolutional neural network ie VGG to …

3D meshes are usually affected by various visual distortions during their transmission and
geometric processing. In this paper we propose a reduced reference method for mesh visual …

We propose in this paper a novel objective method to evaluate the perceived visual quality
of 3D meshes. The proposed method in no-reference, it relies only on the distorted mesh for …

3D meshes have gained significant interest in computer vision community due to their use in
several applications such as virtual reality, gaming, heritage preservation, etc. How-ever …

Blind or No reference quality evaluation is a challenging issue since it is done without
access to the original content. In this work, we propose a method based on deep learning for …

We propose in this work a graph-based deep learning method for mesh visual quality
assessment. To carry out this proposal, we transform a given distorted mesh to a graph …

Blind quality assessment is a challenging issue since the evaluation is done without access
to the reference nor any information about the distortion. In this work, we propose an …

We propose in this paper a novel objective method to evaluate the perceived visual quality
of 3D meshes. The proposed method in no-reference, it relies only on the distorted mesh for …

With the widespread availability and utilization of 3D meshes across various applications,
the need for accurately assessing their visual quality has become increasingly important …

This paper presents a new method for no reference mesh visual quality assessment using a
convolutional neural network. To do this, we first render 2D images from multiple views of …