UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 3 | March 2026

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Published in:

Volume 12 Issue 6
June-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRGW06020


Registration ID:
562690

Page Number

116-122

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Title

ADVANCEMENTS IN NEURAL RADIANCE FIELDS (NERF): A COMPREHENSIVE REVIEW OF 3D SCENE RECONSTRUCTION AND REAL-TIME RENDERING

Abstract

Neural Radiance Fields (NeRF) mark a pivotal advancement in 3D scene reconstruction and real-time rendering. By integrating deep learning with volumetric rendering, NeRF facilitates the creation of highly realistic novel views from limited 2D image inputs. This technology is vital for fields like medical imaging, augmented and virtual reality (AR/VR), and robotics, where precise scene reconstruction and efficient performance are critical. Unlike conventional 3D modeling approaches, which often face issues with scalability, view limitations, and visual fidelity, NeRF and its evolved iterations address these drawbacks through innovative architectures and optimization strategies. This review provides an in-depth exploration of NeRF, covering its theoretical underpinnings, core challenges, and subsequent improvements. We examine recent developments, including MultiPlaneNeRF, Neural Ray- Surface Mapping (NRSM), and self-supervised frameworks for robotics, highlighting how these advancements enable faster, more adaptable, and scalable 3D modeling. Additionally, the paper investigates NeRF’s real-world applications, identifies persistent obstacles ,and suggests potential avenues for future research, such as dynamic scene modeling and optimization for mobile devices. By synthesizing and critically evaluating existing studies, this review seeks to be a valuable resource for researchers and professionals aiming to engage with and advance this groundbreaking field.

Key Words

Neural Radiance Fields, 3D Scene Reconstruction, Real-Time Rendering, Deep Learning, Computer Vision, AR/VR ,Robotics, Medical Imaging.

Cite This Article

"ADVANCEMENTS IN NEURAL RADIANCE FIELDS (NERF): A COMPREHENSIVE REVIEW OF 3D SCENE RECONSTRUCTION AND REAL-TIME RENDERING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 6, page no.116-122, June-2025, Available :http://www.jetir.org/papers/JETIRGW06020.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"ADVANCEMENTS IN NEURAL RADIANCE FIELDS (NERF): A COMPREHENSIVE REVIEW OF 3D SCENE RECONSTRUCTION AND REAL-TIME RENDERING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 6, page no. pp116-122, June-2025, Available at : http://www.jetir.org/papers/JETIRGW06020.pdf

Publication Details

Published Paper ID: JETIRGW06020
Registration ID: 562690
Published In: Volume 12 | Issue 6 | Year June-2025
DOI (Digital Object Identifier):
Page No: 116-122
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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