Neural Radiance Field(NeRF) is an novel implicit method to achieve the 3D reconstruction and representation with a high resolution. After the first research of NeRF is proposed, NeRF has gained a robust developing power and is booming in the 3D modeling, representation and reconstruction areas. However the first and most of the followed research projects based on NeRF is static, which are weak in the practical applications. Therefore, more researcher are interested and focused on the study of dynamic NeRF that is more feasible and useful in practical applications or situations. Compared with the static NeRF, implementing the Dynamic NeRF is more difficult and complex. But Dynamic is more potential in the future even is the basic of Editable NeRF. In this review, we made a detailed and abundant statement for the development and important implementation principles of Dynamci NeRF. The analysis of main principle and development of Dynamic NeRF is from 2021 to 2023, including the most of the Dynamic NeRF projects. What is more, with colorful and novel special designed figures and table, We also made a detailed comparison and analysis of different features of various of Dynamic. Besides, we analyzed and discussed the key methods to implement a Dynamic NeRF. The volume of the reference papers is large. The statements and comparisons are multidimensional. With a reading of this review, the whole development history and most of the main design method or principles of Dynamic NeRF can be easy understood and gained.

翻译：神经辐射场（NeRF）是一种新颖的隐式方法，能够实现高分辨率的3D重建与表示。自NeRF的首项研究提出以来，其在3D建模、表示与重建领域获得了强劲的发展动力，并迅速兴起。然而，最早的NeRF及其大部分后续研究项目均为静态的，在实际应用中存在局限性。因此，更多研究者关注并聚焦于在实际应用或场景中更具可行性和实用性的动态NeRF研究。与静态NeRF相比，实现动态NeRF更为困难且复杂，但动态NeRF在未来更具潜力，甚至可作为可编辑NeRF的基础。在本综述中，我们对动态NeRF的发展及其重要实现原理进行了详细而丰富的阐述。对动态NeRF主要原理与发展的分析涵盖2021年至2023年，包括绝大多数动态NeRF项目。此外，借助新颖独特设计的彩色图表，我们还对多种动态NeRF的不同特征进行了详细比较与分析。同时，我们分析与讨论了实现动态NeRF的关键方法。参考文献数量庞大，陈述与比较均为多维度的。通过阅读本综述，可以轻松理解并掌握动态NeRF的整个发展历史及大部分主要设计方法或原理。