Translation-based Video Synthesis (TVS) has emerged as a vital research area
in computer vision, aiming to facilitate the transformation of videos between
distinct domains while preserving both temporal continuity and underlying
content features. This technique has found wide-ranging applications,
encompassing video super-resolution, colorization, segmentation, and more, by
extending the capabilities of traditional image-to-image translation to the
temporal domain. One of the principal challenges faced in TVS is the inherent
risk of introducing flickering artifacts and inconsistencies between frames
during the synthesis process. This is particularly challenging due to the
necessity of ensuring smooth and coherent transitions between video frames.
Efforts to tackle this challenge have induced the creation of diverse
strategies and algorithms aimed at mitigating these unwanted consequences. This
comprehensive review extensively examines the latest progress in the realm of
TVS. It thoroughly investigates emerging methodologies, shedding light on the
fundamental concepts and mechanisms utilized for proficient video synthesis.
This survey also illuminates their inherent strengths, limitations, appropriate
applications, and potential avenues for future development.

以图像转换为基础的视频合成（TVS）作为计算机视觉中的一个关键研究领域，旨在在保持时间连续性和基础特征的同时促进视频在不同领域之间的转换。本文通过全面回顾最新进展，深入研究新兴方法和机制，阐明了有效视频合成的基本概念。同时，它还探讨了它们的优点、局限性、适用应用和未来发展的潜在方向。