State-space Decomposition Model for Video Prediction Considering Long-term Motion Trend

arXiv:2404.11576v1 Announce Type: new
Abstract: Stochastic video prediction enables the consideration of uncertainty in future motion, thereby providing a better reflection of the dynamic nature of the environment. Stochastic video prediction methods based on image auto-regressive recurrent models need to feed their predictions back into the latent space. Conversely, the state-space models, which decouple frame synthesis and temporal prediction, proves to be more efficient. However, inferring long-term temporal information about motion and generalizing to dynamic scenarios under non-stationary assumptions remains …

abstract arxiv auto cs.cv dynamic environment future image long-term nature prediction predictions space state stochastic the environment trend type uncertainty video