Recent advances in diffusion models have set an impressive milestone in many generation
tasks, and trending works such as DALL-E2, Imagen, and Stable Diffusion have attracted …

Abstract Single Image Super Resolution (SISR) is a process to obtain a high pixel density
and refined details from a low resolution (LR) image to get upscaled and sharper high …

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

We propose semantic region-adaptive normalization (SEAN), a simple but effective building
block for Generative Adversarial Networks conditioned on segmentation masks that describe …

Deep learning-based methods have achieved remarkable success in image restoration and
enhancement, but are they still competitive when there is a lack of paired training data? As …

Abstract Conditional Generative Adversarial Networks (cGAN) generate realistic images by
incorporating class information into GAN. While one of the most popular cGANs is an …

Neural architecture search (NAS) has witnessed prevailing success in image classification
and (very recently) segmentation tasks. In this paper, we present the first preliminary study …

Artistic text generation aims to amplify the aesthetic qualities of text while maintaining
readability. It can make the text more attractive and better convey its expression, thus …

We introduce a simple and versatile framework for image-to-image translation. We unearth
the importance of normalization layers, and provide a carefully designed two-stream …

Existing deep learning real denoising methods require a large amount of noisy-clean image
pairs for supervision. Nonetheless, capturing a real noisy-clean dataset is an unacceptable …