Although no specific domain knowledge is considered in the design, plain vision
transformers have shown excellent performance in visual recognition tasks. However, little …

Vision transformers have shown great potential in various computer vision tasks owing to
their strong capability to model long-range dependency using the self-attention mechanism …

Large-scale vision foundation models have made significant progress in visual tasks on
natural images, with vision transformers (ViTs) being the primary choice due to their good …

Abstract Vision Transformers (ViTs) have triggered the most recent and significant
breakthroughs in computer vision. Their efficient designs are mostly guided by the indirect …

While some studies have proven that Swin Transformer (Swin) with window self-attention
(WSA) is suitable for single image super-resolution (SR), the plain WSA ignores the broad …

Abstract Vision Transformer (ViT) has gained increasing attention in the computer vision
community in recent years. However the core component of ViT Self-Attention lacks explicit …

Vision transformers have become popular as a possible substitute to convolutional neural
networks (CNNs) for a variety of computer vision applications. These transformers, with their …

Single hyperspectral image super-resolution (single-HSI-SR) aims to restore a high-
resolution hyperspectral image from a low-resolution observation. However, the prevailing …

State-of-the-art parametric and non-parametric style transfer approaches are prone to either
distorted local style patterns due to global statistics alignment, or unpleasing artifacts …

The use of pretrained backbones with fine-tuning has been successful for 2D vision and
natural language processing tasks, showing advantages over task-specific networks. In this …