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Neural Radiance Fields for the Real World: A Survey
January 22, 2025 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: Neural Radiance Fields for the Real World: A Survey"
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Authors
Wenhui Xiao, Remi Chierchia, Rodrigo Santa Cruz, Xuesong Li, David Ahmedt-Aristizabal, Olivier Salvado, Clinton Fookes, Leo Lebrat
arXiv ID
2501.13104
Category
cs.CV: Computer Vision
Cross-listed
cs.GR
Citations
10
Venue
arXiv.org
Last Checked
3 days ago
Abstract
Neural Radiance Fields (NeRFs) have remodeled 3D scene representation since release. NeRFs can effectively reconstruct complex 3D scenes from 2D images, advancing different fields and applications such as scene understanding, 3D content generation, and robotics. Despite significant research progress, a thorough review of recent innovations, applications, and challenges is lacking. This survey compiles key theoretical advancements and alternative representations and investigates emerging challenges. It further explores applications on reconstruction, highlights NeRFs' impact on computer vision and robotics, and reviews essential datasets and toolkits. By identifying gaps in the literature, this survey discusses open challenges and offers directions for future research.
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