CFAT: Unleashing TriangularWindows for Image Super-resolution

arXiv:2403.16143v1 Announce Type: cross
Abstract: Transformer-based models have revolutionized the field of image super-resolution (SR) by harnessing their inherent ability to capture complex contextual features. The overlapping rectangular shifted window technique used in transformer architecture nowadays is a common practice in super-resolution models to improve the quality and robustness of image upscaling. However, it suffers from distortion at the boundaries and has limited unique shifting modes. To overcome these weaknesses, we propose a non-overlapping triangular window technique that synchronously works …

abstract architecture arxiv cs.cv cs.lg cs.mm eess.iv features however image practice quality resolution robustness transformer transformer architecture type upscaling