3D reconstruction techniques involve using digital tools to create a three-dimensional representation of a physical object or environment. This approach has many benefits, including the ability to preserve cultural heritage sites that may be at risk of damage or destruction, as well as providing greater access to these sites for people who may not be able to visit them in person. Neural Radiance Fields (NeRF) is a technique for 3D reconstruction that uses a deep neural network to model the volumetric density and color of a scene. The NeRF model is trained using a set of input images of the scene, along with corresponding camera positions and orientations. During training, the network is optimized to minimize the difference between the predicted and ground truth colors of the scene at the observed camera viewpoints. Resultant values produce the 3D surfaces of the artifacts of the scanned models to create the virtual environment.