As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

Since convolutional neural networks (CNNs) perform well at learning generalizable image
priors from large-scale data, these models have been extensively applied to image …

This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …

Astounding results from Transformer models on natural language tasks have intrigued the
vision community to study their application to computer vision problems. Among their salient …

The recent explosive interest on transformers has suggested their potential to become
powerful``universal" models for computer vision tasks, such as classification, detection, and …

Challenging illumination conditions (low-light, under-exposure and over-exposure) in the
real world not only cast an unpleasant visual appearance but also taint the computer vision …

Transformers, the dominant architecture for natural language processing, have also recently
attracted much attention from computational visual media researchers due to their capacity …

We show that raw degradation features can effectively guide deep restoration models,
providing accurate degradation priors to facilitate better restoration. While networks that do …

Anomaly detection is an active research field in industrial defect detection and medical
disease detection. However, previous anomaly detection works suffer from unstable training …