Diffusion models excel at producing high-quality samples but naively require hundreds of
iterations, prompting multiple attempts to distill the generation process into a faster network …

Diffusion model-based image restoration (IR) aims to use diffusion models to recover high-
quality (HQ) images from degraded images achieving promising performance. Due to the …

Deformable image registration (DIR) is an active research topic in biomedical imaging.
There is a growing interest in developing DIR methods based on deep learning (DL). A …

Deep equilibrium (DEQ) models are widely recognized as a memory efficient alternative to
standard neural networks, achieving state-of-the-art performance in language modeling and …

Image dehazing has drawn a significant attention in recent years. Learning-based methods
usually require paired hazy and corresponding ground truth (haze-free) images for training …

In recent years, deep learning based feature fusion has drawn significant attention in the
field of information integration due to its robust representational and generative capabilities …