  3D Gaussian splatting (GS) has recently emerged as a transformative technique
in the realm of explicit radiance field and computer graphics. This innovative
approach, characterized by the utilization of millions of learnable 3D
Gaussians, represents a significant departure from mainstream neural radiance
field approaches, which predominantly use implicit, coordinate-based models to
map spatial coordinates to pixel values. 3D GS, with its explicit scene
representation and differentiable rendering algorithm, not only promises
real-time rendering capability but also introduces unprecedented levels of
editability. This positions 3D GS as a potential game-changer for the next
generation of 3D reconstruction and representation. In the present paper, we
provide the first systematic overview of the recent developments and critical
contributions in the domain of 3D GS. We begin with a detailed exploration of
the underlying principles and the driving forces behind the emergence of 3D GS,
laying the groundwork for understanding its significance. A focal point of our
discussion is the practical applicability of 3D GS. By enabling unprecedented
rendering speed, 3D GS opens up a plethora of applications, ranging from
virtual reality to interactive media and beyond. This is complemented by a
comparative analysis of leading 3D GS models, evaluated across various
benchmark tasks to highlight their performance and practical utility. The
survey concludes by identifying current challenges and suggesting potential
avenues for future research in this domain. Through this survey, we aim to
provide a valuable resource for both newcomers and seasoned researchers,
fostering further exploration and advancement in applicable and explicit
radiance field representation.
