Resolving Spatio-Temporal Entanglement in Video Prediction via Multi-Modal Attention

ArXi:2501.16997v2 Announce Type: replace-cross The fast progress in computer vision has necessitated advanced methods for temporal sequence modeling. This area is essential for the operation of autonomous systems, real-time surveillance, and predicting anomalies. As the demand for accurate video prediction increases, the limitations of traditional deterministic models, particularly their struggle to maintain long-term temporal coherence while providing high-frequency spatial detail, have become very clear.