Evaluating 3D Reconstruction: A Side-by-Side Comparison of NeRF and Gaussian Splatting in Indoor and Outdoor Environments

This study presents a comparative evaluation of Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) for 3D reconstruction in indoor and outdoor environments. High-quality 3D models are significant in a range of applications, from forensic investigations to cultural heritage preservation, architecture, and robotics, where detail accuracy and minimal noise are crucial. Leveraging continuous video footage captured with a stabilized full-frame camera setup, this research examines both algorithms across indoor and outdoor environments using consistent datasets. Key assessment criteria include reconstruction noise, detail preservation, and processing time. The results reveal that while both approaches generate high fidelity reconstructions, 3DGS outperforms NeRF in computational efficiency and noise reduction. These insights provide valuable guidance for selecting suitable reconstruction techniques across different professional domains. Due to the controlled scope and limited number of test scenes, the findings should be interpreted as indicative rather than statistically generalizable, serving primarily as a practical, application-oriented comparison.