We present a framework for video modeling based on denoising diffusion probabilistic
models that produces long-duration video completions in a variety of realistic environments …

Denoising diffusion probabilistic models are a promising new class of generative models
that mark a milestone in high-quality image generation. This paper showcases their ability to …

Despite the remarkable progress in deep generative models, synthesizing high-resolution
and temporally coherent videos still remains a challenge due to their high-dimensionality …

Video prediction is a challenging task. The quality of video frames from current state-of-the-
art (SOTA) generative models tends to be poor and generalization beyond the training data …

Generative models that can model and predict sequences of future events can, in principle,
learn to capture complex real-world phenomena, such as physical interactions. However, a …

Generative models that can model and predict sequences of future events can, in principle,
learn to capture complex real-world phenomena, such as physical interactions. In particular …

Despite tremendous progress in generating high-quality images using diffusion models,
synthesizing a sequence of animated frames that are both photorealistic and temporally …

Text-conditioned diffusion models have emerged as a promising tool for neural video
generation. However, current models still struggle with intricate spatiotemporal prompts and …

Predicting future video frames is extremely challenging, as there are many factors of
variation that make up the dynamics of how frames change through time. Previously …

VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation Page 1
VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation *Zhengxiong …