MuSt-NeRF: A Multi-Stage NeRF Pipeline to Enhance Novel View Synthesis

Sudarshan Raghavan Iyengar, Subash Sharma, Patrick Vandewalle

2025

Abstract

Neural Radiance Fields (NeRFs) have emerged as a powerful technique for novel view synthesis, but accurately capturing both intricate geometry and complex view-dependent effects, especially in challenging real-world scenes, remains a limitation of existing methods. This work presents MuSt-NeRF, a novel multi-stage pipeline designed to enhance the fidelity and robustness of NeRF-based reconstructions. The approach strategically chains complementary NeRF architectures, organized into two stages: a depth-guided stage that establishes a robust geometric foundation, followed by a refinement stage that enhances details and accurately renders view-dependent effects. Crucially, MuSt-NeRF allows flexible stage ordering, enabling either geometry-first or photometry-first reconstruction based on scene characteristics and desired outcomes. Experiments on diverse datasets, including synthetic scenes and complex indoor environments from the ScanNet dataset, demonstrate that MuSt-NeRF consistently outperforms single-stage NeRF and 3D Gaussian Splatting methods, achieving higher scores on established metrics like PSNR, SSIM, and LPIPS, while producing visually superior reconstructions. MuSt-NeRF’s flexibility and robust performance make it a promising approach for high-fidelity novel view synthesis in complex, real-world scenes. The code is made available at https://github.com/sudarshan-iyengar/MuSt-NeRF.

Paper Citation

in Harvard Style

Iyengar S., Sharma S. and Vandewalle P. (2025). MuSt-NeRF: A Multi-Stage NeRF Pipeline to Enhance Novel View Synthesis. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 563-573. DOI: 10.5220/0013169100003912

in Bibtex Style

@conference{visapp25,
author={Sudarshan Iyengar and Subash Sharma and Patrick Vandewalle},
title={MuSt-NeRF: A Multi-Stage NeRF Pipeline to Enhance Novel View Synthesis},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2025},
pages={563-573},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013169100003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - MuSt-NeRF: A Multi-Stage NeRF Pipeline to Enhance Novel View Synthesis
SN - 978-989-758-728-3
AU - Iyengar S.
AU - Sharma S.
AU - Vandewalle P.
PY - 2025
SP - 563
EP - 573
DO - 10.5220/0013169100003912
PB - SciTePress