Research Library

open-access-imgOpen AccessMethods and strategies for improving the novel view synthesis quality of neural radiation field
Author(s)
Shun Fang,
Ming Cui,
Xing Feng,
YanNa Lv
Publication year2024
Publication title
ieee access
Resource typeMagazines
PublisherIEEE
Neural Radiation Field (NeRF) technology can learn a 3D implicit model of a scene from 2D images and synthesize realistic novel view images. This technology has received widespread attention from the industry and has good application prospects. In response to the problem that the rendering quality of NeRF images needs to be improved, many researchers have proposed various methods to improve the rendering quality in the past three years. The latest relevant papers are classified and reviewed, the technical principles behind quality improvement are analyzed, and the future evolution direction of quality improvement methods is discussed. This study can help researchers quickly understand the current state and evolutionary context of technology in this field, which is helpful in inspiring the development of more efficient algorithms and promoting the application of NeRF technology in related fields.
Subject(s)aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Keyword(s)Rendering (computer graphics), Image color analysis, Three-dimensional displays, Image reconstruction, Training, Lighting, Training data, 3D reconstruction, New view synthesis, Neural Radiation Field, Volume rendering
Language(s)English
SCImago Journal Rank0.587
H-Index127
eISSN2169-3536
DOI10.1109/access.2024.3382997

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