 This paper presents a new type of generative model called denoising diffusion probabilistic models that can generate high-quality video by sequentially correcting a deterministic next frame prediction with a stochastic residual generated through an inverse diffusion process, outperforming prior methods in perceptual and probabilistic forecasting metrics. This article was authored by Ruohen Yang, Preker Shrivastava, and Stefan Mant.