The technology integrated with Artificial Intelligence functionality allows the acquisition of real spaces in an increasingly expeditious manner, giving the possibility of digitally configuring complex environments and experimenting with new digital surveying methodologies that differ from the established image/range-based techniques. In recent years, substantial advancements in the fields of computer graphics and computer vision have led to the emergence of innovative approaches, such as Gaussian Splatting, which have revolutionized 3D scene reconstruction and rendering processes. These methods offer remarkable improvements in both realism and computational efficiency. Moreover, in the digital age, the demand for accessible and user-friendly applications is constantly growing, and research is increasingly focused on solutions that offer essential functionality at cost-effective prices. These objectives are mainly pursued by exploiting open-source frameworks, cloud services, and simple methodologies to keep development costs low. The paper aims to validate the results of two Gaussian Splatting processes generated by accessible and user-friendly applications, as well as using simple data as a starting point, such as videos recorded with 360-degree cameras. In this way, the work seeks to evaluate the effectiveness of these innovative techniques in producing high-quality 3D reconstructions, considering the simplicity of the process for users and the associated costs.
Integration of AI-Based Methodologies for Surveying and Virtual Reconstruction: The Case of the Chiostro and the Cappella della Pace in the Monastery of Santi Giovanni e Paolo in Venice
The case study described below is part of a larger project entitled “RE-LIFE: accessibility and inclusiveness in the scenarios of reuse and enhancement of former monastic buildings” at the University of Padua, funded by the European Commission and still under development. The project involves the use of Building Information Modelling (BIM) reconstruction, historical-architectural analysis, accessibility studies, and the use of virtual and augmented reality to highlight, through a timeline, the various construction phases and works lost over the centuries. The present article focuses on the case of Santi Giovanni e Paolo and on the Chiostro and Cappella della Pace, both of which no longer survive. The objective of the article is to delineate the historical and graphic workflow pursued to reconstruct the chapel, a hypothesis based on the analysis of precise historical-graphic sources and on the digital survey. The latter was carried out on the cloister through photogrammetry using a Fujifilm MILC camera and an Insta360 X4 8K. The focus is on the use of 360 video shooting techniques for photogrammetric survey processing and on the possibility of integrating a Gaussian Splatting survey for the development of immersive realities, such as applied games or virtual tours. The article provides a comprehensive explanation of how diverse representation techniques can be converged for a singular divulgative purpose.
The Former Monastery of Saints Severino and Sossio: An Example of an Immersive Reality for the Dissemination of Cultural Heritage
The paper presents an immersive digital reconstruction of the former monastery of Saints Severino and Sossio, currently housing the State Archive of Naples, aimed at enhancing cultural heritage dissemination. The methodology integrates historical research, archival documentation, and multi-source digital survey techniques, including photogrammetry, laser scanning, LiDAR, and AI-based approaches such as NeRF and Gaussian Splatting. The resulting 3D model is implemented within a real-time interactive environment using Unreal Engine 5, where advanced rendering technologies (Nanite and Lumen) enable highly detailed and photorealistic visualization. The system is structured as an applied game, allowing users to navigate the architectural complex and explore its historical transformations through a timeline-based interaction. The research highlights the potential of AI-driven workflows and immersive environments to accelerate data acquisition, improve visualization quality, and support both analysis and dissemination of cultural heritage.
Neural Networks as an Alternative to Photogrammetry. Using Instant NeRF and Volumetric Rendering
This paper investigates Neural Radiance Fields (NeRF) as an emerging alternative to traditional photogrammetry for the digital acquisition of heritage objects and environments. The study reviews recent developments in machine learning and computer vision, focusing on NVIDIA Instant NeRF, volumetric rendering, and related platforms such as Luma AI and Nerfstudio. Unlike conventional photogrammetry, NeRF systems reconstruct scenes through neural networks that infer missing views and generate volumetric representations with realistic lighting, reflections, and textures. The authors test these methods on a sculptural case study, evaluating speed, geometric quality, mesh extraction, texture generation, and interoperability with external software such as Blender and Unreal Engine. Results show that NeRF workflows can reduce acquisition and processing times while performing particularly well on reflective materials and complex lighting conditions, areas where photogrammetry often struggles. Although current outputs still present limitations in mesh closure, topology control, and metric reliability, the research suggests that neural rendering may soon become a powerful tool for digital twins, immersive heritage visualization, and future survey practices.
Making the Invisible Visible: Virtual/Interactive Itineraries in Roman Padua
PD–Invisible aims to enhance the archaeological heritage of Padua hidden by urban development. The focus of the process is the creation of an adaptive AR App according to the type of user: professionals and researchers on the one hand and cultural tourism on the other. The workflow identifies a path through the city and connects the artifacts studied by the research; catalogue historical and archival documents; detects the structures through laser scanning and photogrammetry technologies; opti-mizes the acquired models both from a graphic point of view and through Scan to BIM; develops the AR App in Unity 3D. The research offers further insights assuming the use of artificial intelligence for this type of applications: differentiate the contents of the App according to the user’s preferences by comparing the GPS data with those of the detection devices (camera and Lidar).