Enhanced Spatiotemporal Prediction Using Physical-guided And Frequency-enhanced Recurrent Neural Networks

arXiv:2405.14504v1 Announce Type: new
Abstract: Spatiotemporal prediction plays an important role in solving natural problems and processing video frames, especially in weather forecasting and human action recognition. Recent advances attempt to incorporate prior physical knowledge into the deep learning framework to estimate the unknown governing partial differential equations (PDEs), which have shown promising results in spatiotemporal prediction tasks. However, previous approaches only restrict neural network architectures or loss functions to acquire physical or PDE features, which decreases the representative capacity …

abstract action action recognition advances arxiv cs.ai cs.cv deep learning deep learning framework differential forecasting framework human knowledge natural networks neural networks prediction prior processing recognition recurrent neural networks role the unknown type video weather weather forecasting