Face super-resolution aims to reconstruct a high-resolution face image from a low-resolution
face image. Previous methods typically employ an encoder-decoder structure to extract …

In single-image super-resolution (SISR) tasks, many methods benefit from the local and
global contexts of the image. Despite that, no methods use the bidirectional interaction …

Single-image super-resolution (SISR) seeks to elucidate the mapping relationships between
low-resolution and high-resolution images. However, high-performance network models …

Since the global self-attention mechanism can capture long-distance dependencies well,
Transformer-based methods have achieved remarkable performance in many vision tasks …

In recent research, single-image super-resolution (SISR) using deep Convolutional Neural
Networks (CNN) has seen significant advancements. While previous methods excelled at …

Recently, CNN and Transformer hybrid networks demonstrated excellent performance in
face super-resolution (FSR) tasks. Since numerous features at different scales in hybrid …

Image High Resolution takes a principal function to the region of the photograph filtering to
enhance the photograph and video frames for Enhanced Resolution in gadgets such as …