Future Frame Prediction

Future frame prediction aims to generate realistic video sequences depicting events subsequent to an observed input, primarily focusing on improving accuracy and temporal consistency. Current research emphasizes the development of sophisticated models, including diffusion models adapted for video, neural velocity fields capturing 3D scene dynamics, and hierarchical recurrent networks handling multiple spatio-temporal scales, often incorporating techniques like optical flow and semantic segmentation. These advancements have implications for various applications, such as video anomaly detection, autonomous systems, and weather forecasting, by enabling more robust and accurate predictions of future events.