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.

NeRF 技术可以从 2D 图像中学习场景的 3D 隐式模型，并合成逼真的新视角图像。本研究分析了过去三年中涉及 NeRF 图像渲染质量改进的最新相关论文，探讨了质量改进方法背后的技术原理，并讨论了质量改进方法未来的演进方向，有助于研究人员快速了解该领域技术的当前状态和演进背景，对于激发更高效算法的开发和推动 NeRF 技术在相关领域的应用具有帮助。