Evaluating Human Aesthetic and Emotional Aspects of 3D generated content through eXtended Reality

The Metaverse era is rapidly shaping novel and effective tools particularly useful in the entertainment and creative industry. A fundamental role is played by modern generative deep learning models, that can be used to provide varied and high-quality multimedia content, considerably lowering costs while increasing production efficiency. The goodness of such models is usually evaluated quantitatively with established metrics on data and humans using simple constructs such as the Mean Opinion Score. However, these scales and scores don't take into account the aesthetical and emotional components, which could play a role in positively controlling the automatic generation of multimedia content while at the same time introducing novel forms of human-in-the-loop in generative deep learning. Furthermore, considering data such as 3D models/scenes, and 360° panorama images and videos, conventional display hardware may not be the most effective means for human evaluation. A first solution to such a problem could consist of employing eXtendend Reality paradigms and devices. Considering all such aspects, we here discuss a recent contribution that adopted a well-known scale to evaluate the aesthetic and emotional experience of watching a 360° video of a musical concert in Virtual Reality (VR) compared to a classical 2D webstream, showing that adopting fully immersive VR experience could be a possible path to follow.