Artificial intelligence for graphs has achieved remarkable success in modelling complex
systems, ranging from dynamic networks in biology to interacting particle systems in physics …

Over the last decade, the number of digital images captured per day has increased
exponentially, due to the accessibility of imaging devices. The visual quality of photographs …

Image restoration technology is a crucial field in image processing and is extensively utilized
across various domains. Recently, with advancements in graph convolutional network …

Multi-scale architectures have shown effectiveness in a variety of tasks thanks to appealing
cross-scale complementarity. However, existing architectures treat different scale features …

Super-Resolution (SR) reconstructs high-resolution images from low-resolution ones. CNNs
and window-attention methods are two major categories of canonical SR models. However …

Atmospheric turbulence-degraded images in typical practical application scenarios are
always disturbed by severe additive noise. Severe additive noise corrupts the prior …

Few-shot object detection is an important but challenging task where only a few instances of
novel categories are available. The widely used approach is to pretrain a detector on base …

Image restoration refers to the process of inspecting a degraded image and recovering the
underlying artifact-free counterpart through discarding the artifacts. Medical image …