Space-Time Video Super-Resolution with Efficient Motion Estimation and Compensation

The proposed Space-Time Neural Operator (STNO) effectively extracts fine-grained spatiotemporal representations from coarse-grained intra-frame features by modeling the task as a mapping between two continuous function spaces. The Galerkin-type attention mechanism in STNO enables precise and efficient motion estimation and compensation, particularly for large motions.