We provide a large dataset of 480 animated meshes with diffuse color information, and associated with perceived quality judgments. The stimuli were generated from 5 source models subjected to geometry and color distortions. Each stimulus was associated with 6 hypothetical rendering trajectories (HRTs): combinations of 3 viewpoints and 2 animations. This dataset is the largest one for quality assessment of 3D contents with diffuse color, and the first based on vertex color representation. It is also the first public dataset produced in VR for such data (see the "Dataset" folder).

The subjctive data, collected by our subjective experiment, allowed us to explore the influence of source models, animations and viewpoints on both the quality scores (MOSs) and their confidence intervals (CIs). In order to do this, we carried out a quantitative analysis, provided in the "Statistical_Analysis" folder.

The results are shown in the "Results" folder.

This work refers to the following publication: Y. Nehmé, F. Dupont, J. Farrugia, P. Le Callet and G. Lavoue, "Visual Quality of 3D Meshes with Diffuse Colors in Virtual Reality: Subjective and Objective Evaluation" in IEEE Transactions on Visualization & Computer Graphics (TVCG), vol. 27, no. 03, 2021. doi: 10.1109/TVCG.2020.3036153