This paper describes a new generation technique for creating videos with text-to-text models.
Earlier, scientists had tried to use diffusion models to create video with text prompts.
However, they were not very good at controlling the generated content.
This paper presents a new approach that uses a controllable T2V model to achieve high-quality and consistency in video-creation.
The authors claim that this new approach can be used to reduce the time it takes to generate videos with higher resolutions and greater variety.
Video-ControlNet, a new version of the diffusion model used in this paper, solves one of the bottlenecks inherent in the early generation of video data by providing control over the amount of information that is fed into the model.
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