Neural Radiance Fields for the Real World: A Survey

ACM Computing Surveys 2026 Open access

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Authors: Wenhui Xiao, Remi Chierchia, Rodrigo Santa Cruz, Xuesong Li, David Ahmedt‐Aristizabal, Olivier Salvado, Clinton Fookes, Léo Lebrat
DOI: 10.1145/3837758
Cited by: 1
References: 230

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 scene 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.

Fields of Study & Subjects

Functional Brain Connectivity Studies CCD and CMOS Imaging Sensors Visual perception and processing mechanisms

Publication details

Journal / source
ACM Computing Surveys
Publisher
Association for Computing Machinery (ACM)
Volume
58
Issue
15
Pages
1–36
Publication date
1 August 2026
Language
EN