NERF FOR HERITAGE 3D RECONSTRUCTION

36 citations as recorded by crossref.

1. GAT-NeRF: Geometry-Aware-Transformer-Enhanced Neural Radiance Fields for High-Fidelity 4D Facial Avatars Z. Chang et al. https://doi.org/10.1145/3770086
2. PG-SAG: Parallel Gaussian Splatting for Fine-Grained Large-Scale Urban Buildings Reconstruction via Semantic-Aware Grouping T. Wang et al. https://doi.org/10.1007/s41064-025-00343-0
3. Perceptual Quality Assessment for NeRF-Generated Scenes: A Training Reference Metric S. Luo et al. https://doi.org/10.1109/ACCESS.2025.3603970
4. Comparative Assessment of Neural Radiance Fields and Photogrammetry in Digital Heritage: Impact of Varying Image Conditions on 3D Reconstruction V. Croce et al. https://doi.org/10.3390/rs16020301
5. Enhancing Cultural Heritage Accessibility Through Three-Dimensional Artifact Visualization on Web-Based Open Frameworks S. Rattanarungrot et al. https://doi.org/10.3390/informatics12020037
6. High fidelity three dimensional reconstruction and interactive visualization of public art sculptures using neural radiance fields D. Shen https://doi.org/10.1007/s44163-026-02441-3
7. Immersive heritage through Gaussian Splatting: a new visual aesthetic for reality capture O. Jamil & A. Brennan https://doi.org/10.3389/fcomp.2025.1515609
8. Neural Radiance Fields: Driven Exploration of Visual Communication and Spatial Interaction Design for Immersive Digital Installations W. Li & Y. Hu https://doi.org/10.3390/jimaging11110411
9. Digital Recording of Historical Defensive Structures in Mountainous Areas Using Drones: Considerations and Comparisons L. Barazzetti et al. https://doi.org/10.3390/drones7080512
10. An evaluation of DUSt3R/MASt3R/VGGT 3D reconstruction on photogrammetric aerial blocks X. Wu et al. https://doi.org/10.1080/10095020.2025.2597491
11. Efficient 3D reconstruction of heritage monuments using symmetry-aware part-based modeling B. Sharma & S. Jana https://doi.org/10.1007/s00371-026-04669-7
12. Comparison of NeRF- and SfM-Based Methods for Point Cloud Reconstruction for Small-Sized Archaeological Artifacts M. Maté-González et al. https://doi.org/10.3390/rs17142535
13. A deep learning-based pipeline for the conservation assessment of bindings in archives and libraries V. Lee-Gouet et al. https://doi.org/10.1007/s11042-025-20615-6
14. Automatic Removal of Non-Architectural Elements in 3D Models of Historic Buildings with Language Embedded Radiance Fields A. Rusnak et al. https://doi.org/10.3390/heritage7060157
15. AI tools for generating Digital Heritage Twins enhancing storytelling in educational games N. Kilis et al. https://doi.org/10.1016/j.daach.2025.e00451
16. Evaluating the Point Cloud of Individual Trees Generated from Images Based on Neural Radiance Fields (NeRF) Method H. Huang et al. https://doi.org/10.3390/rs16060967
17. Semantic Enrichment of Architectural Heritage Point Clouds Using Artificial Intelligence: The Palacio de Sástago in Zaragoza, Spain M. Buldo et al. https://doi.org/10.3390/heritage7120321
18. Comparative Analysis of 3D Reconstruction Results Using MVS and NeRF: Insights from PCA M. Maharani et al. https://doi.org/10.1088/1755-1315/1486/1/012020
19. Generative AI and 3D Heritage Virtual Reconstructions: A Pragmatic Review M. Lombardi et al. https://doi.org/10.3390/heritage9070246
20. Digitalización 3D en patrimonio industrial: retos metodológicos en el marco de una propuesta participativa O. Lucia Sokol & J. Servera https://doi.org/10.5565/rev/tda.161
21. GeoThangka Net for single-view 3D reconstruction of Thangka principal deities X. Guo et al. https://doi.org/10.1038/s40494-026-02672-8
22. Heritage3DMtl: An Open Multi-Modal UAV Dataset of Montreal’s Diverse Heritage Buildings for Research R. Shende et al. https://doi.org/10.1145/3857220
23. Evaluating Neural Radiance Fields for 3D Plant Geometry Reconstruction in Field Conditions M. Arshad et al. https://doi.org/10.34133/plantphenomics.0235
24. High-resolution multi-view stereo with multi-scale feature fusion D. Chen et al. https://doi.org/10.1016/j.engappai.2025.111231
25. Multi‐tiling neural radiance field (NeRF)—geometric assessment on large‐scale aerial datasets N. Xu et al. https://doi.org/10.1111/phor.12498
26. An ethical framework for trustworthy Neural Rendering applied in cultural heritage and creative industries L. Stacchio et al. https://doi.org/10.3389/fcomp.2024.1459807
27. RAS-NeRF for novel view synthesis of complex reflective artifacts Y. Wang et al. https://doi.org/10.1038/s40494-025-01727-6
28. An Improved Method for 3D Style Transfer of Cliff Carvings Based on Gaussian Splatting Y. Li et al. https://doi.org/10.3390/mca31020047
29. Enhancing cultural heritage digitalization through 3D graphics algorithm and immersive visual communication technology F. Yuan https://doi.org/10.22630/MGV.2026.35.1.1
30. GloNeRF: Boosting NeRF capabilities and multi-view consistency in low-light environments Z. Liu et al. https://doi.org/10.1016/j.cag.2025.104209
31. 3D reconstruction of cultural heritage sites; A case study of Patan Durbar Square P. Shrestha et al. https://doi.org/10.1016/j.daach.2025.e00492
32. Landscape Reconstruction with Earth-and-Timber Medieval Stronghold—Immersive Geovisualization J. Zawadzki & B. Medyńska-Gulij https://doi.org/10.3390/land13081323
33. A comparative framework for neural rendering and photogrammetry for spherical images E. Balloni et al. https://doi.org/10.1007/s12518-026-00762-7
34. Bridging the past and present: AI-driven 3D restoration of degraded artefacts for museum digital display R. Stoean et al. https://doi.org/10.1016/j.culher.2024.07.008
35. A Critical Analysis of NeRF-Based 3D Reconstruction F. Remondino et al. https://doi.org/10.3390/rs15143585
36. 3D mesh colorization from a single image via geometry prior modulation R. Bastola Neupane et al. https://doi.org/10.1016/j.knosys.2025.114578