3 accepted papers
This paper presents MetricGrids, a novel grid-based neural representation that combines elementary metric grids in various metric spaces to approximate complex nonlinear signals. While grid-based representations are widely adopted for their efficiency and scalability, the existing feature grids with…
Federated Learning (FL) has emerged as a promising approach to enable collaborative learning among multiple clients while preserving data privacy. However, cross-domain FL tasks, where clients possess data from different domains or distributions, remain a challenging problem due to the inherent hete…
Deep learning based compressed video quality enhancement has raised lots of interest recently. To explore the information over multiple frames, deformable convolution has been used for temporal alignment. However, in the existing methods, the deformable convolution is used in a relatively naïve way,…