Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation. (arXiv:2205.09853v1 [cs.CV])

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 is difficult. Furthermore, existing
prediction frameworks are typically not capable of simultaneously handling
other video-related tasks such as unconditional generation or interpolation. In
this work, we devise a general-purpose framework called Masked Conditional
Video Diffusion (MCVD) for all of these video synthesis tasks using a
probabilistic conditional score-based denoising diffusion model, conditioned on …

arxiv cv diffusion generation prediction video