Medical imaging methods, such as CT scans, MRI scans, X-rays, and ultrasound imaging,
are widely used for diagnosis in the healthcare domain. However, these methods are often …

Shadow removal is an important computer vision task, whose aim is to successfully detect
the shadow affected area appearing through light occlussion, followed by a photo-realistic …

How to aggregate spatial information plays an essential role in learning-based image
restoration. Most existing CNN-based networks adopt static convolutional kernels to encode …

In image denoising networks, feature scaling is widely used to enlarge the receptive field
size and reduce computational costs. This practice, however, also leads to the loss of high …

Scanning electron microscope (SEM) enables imaging of micro-nano scale objects. It is an
analytical tool widely used in the material, earth and life sciences. However, SEM images …

Abstract Diffusion Probabilistic Models (DPMs) have recently shown remarkable
performance in image generation tasks, which are capable of generating highly realistic …

Multi-stage architectures have exhibited efficacy in image dehazing, which usually
decomposes a challenging task into multiple more tractable sub-tasks and progressively …

Arbitrary style transfer has been demonstrated to be efficient in artistic image generation.
Previous methods either globally modulate the content feature ignoring local details, or …

Image denoising is a critical component in a camera's Image Signal Processing (ISP)
pipeline. There are two typical ways to inject a denoiser into the ISP pipeline: applying a …

Cross-spectral image guided denoising has shown its great potential in recovering clean
images with rich details, such as using the near-infrared image to guide the denoising …