  The rapid development of diffusion models (DMs) has significantly advanced
image and video applications, making "what you want is what you see" a reality.
Among these, video editing has gained substantial attention and seen a swift
rise in research activity, necessitating a comprehensive and systematic review
of the existing literature. This paper reviews diffusion model-based video
editing techniques, including theoretical foundations and practical
applications. We begin by overviewing the mathematical formulation and image
domain's key methods. Subsequently, we categorize video editing approaches by
the inherent connections of their core technologies, depicting evolutionary
trajectory. This paper also dives into novel applications, including
point-based editing and pose-guided human video editing. Additionally, we
present a comprehensive comparison using our newly introduced V2VBench.
Building on the progress achieved to date, the paper concludes with ongoing
challenges and potential directions for future research.
