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

As VR devices become increasingly prevalent, live 360-degree video has surged in
popularity. However, current live 360-degree video systems heavily rely on uplink bandwidth …

Abstract High-resolution Magnetic Resonance Imaging (MRI) is pivotal in both diagnosing
and treating brain tumors, assisting physicians in diagnosis and treatment by displaying …

Recently, Transformer-based techniques have demonstrated impressive effectiveness
across various high-and low-level vision tasks by leveraging the self-attention mechanism …

Diffusion models significantly improve the quality of super-resolved images with their
impressive content generation capabilities. However, the huge computational costs limit the …

Neural Radiance Fields (NeRF) have shown promise in novel view synthesis, but it still face
challenges when applied to refractive objects. The presence of refraction disrupts multiview …

Recent advances in learning-based image compression typically come at the cost of high
complexity. Designing computationally efficient architectures remains an open challenge. In …

In recent years, convolutional neural networks (CNNs) have made significant strides in
single image super-resolution (SISR). However, redundancy persists in network models …

Transformer, composed of self-attention and Feed-Forward Network, has revolutionized the
landscape of network design across various vision tasks. FFN is a versatile operator …

This article proposes an interactive-interpretable network (IIN) to facilitate accurately
zooming in the low-resolution scanning electron microscopy (SEM) image data which could …