### Technological Context and Related Research  
Virtual environments, computer-generated 3D simulations, enable the exploration and manipulation of digital worlds, offering advantages such as access to information from anywhere and the development of skills like creativity and critical thinking. Despite their benefits, it is crucial to consider potential negative effects, such as vision problems or software dependence, requiring careful design and attention to updates to ensure compatibility with specific goals [1]. In the industrial context, these virtual environments play a crucial role in training and decision-making, providing professionals with a secure and controlled environment for studying complex processes [2]. The concept of the metaverse, a shared virtual space for the creation and experience of interactive virtual worlds, has sparked controversy. Its increasing relevance in areas such as entertainment, education [3], and industry is highlighted [4]. In Figure 1, an example illustrates what a metaverse looks like and how avatars are visualized. Current advancements are crucial for the future of the metaverse, as mentioned in [5]. The emphasis lies in enhancing aspects such as reducing latency for seamless interactions, acquiring high-quality data to ensure an immersive and precise experience, and crafting virtual worlds that are more realistic and interactive, among other considerations. In the industrial context, the metaverse offers advantages such as product visualization, worker training, and effective communication, but high-quality virtual models that accurately reproduce the physical and visual characteristics of real objects are required [6]. Currently, 3D technologies have experienced exponential growth, reshaping various sectors of modern society, including entertainment [7], education [8], medicine [9], and culture [10]. These technologies have fundamentally altered how humans perceive and engage with the world around them. The creation of 3D models, which includes detailed  
Figure 1: Example of interaction in the metaverse: virtual visit to Valencia city in the following. [[https://www.spatial.io/s/Visit-Valencia-639b11](https://www.spatial.io/s/Visit-Valencia-639b11) ab10f4070001b4a87b?share=85202435970757]([https://www.spatial.io/s/Visit-Valencia-639b11](https://www.spatial.io/s/Visit-Valencia-639b11) ab10f4070001b4a87b?share=85202435970757) 64882 (accessed on 19 February 2024). (**a**) Users interacting with elements in the metaverse. (**b**) Customized avatars. information about the geometry, textures, and physical properties of 3D objects, presents a notable challenge in the realms of computer graphics and artificial vision. Choosing the most fitting 3D modeling technique to fulfill the specific requirements of an application is not always a straightforward task. Despite the apparent simplicity of crafting a basic 3D model, producing an accurate and photorealistic computer model of a complex object continues to demand substantial effort [11]. This complexity amplifies when attempting to capture reflections and intricate details of the model. In the realm of virtual reality, an innovative concept has captured the scientific community's attention. This concept is the NeRF, a promising technique for generating highly detailed and realistic virtual content (see an example in Figure 2). This method represents a scene using a fully connected deep neural network, known as a multilayer perceptron (MLP). Its input is a single continuous coordinate in five dimensions, i.e., spatial location (x, y, z) and viewing direction (\(\theta\), \(\phi\)), and its output is the volumetric density and emitted radiance (light intensity) dependent on the view at that spatial location [12]. In other words, it is a technique that employs Artificial Intelligence to achieve highly realistic and detailed results by calculating the camera position and the light intensity it receives.