As realistic facial manipulation technologies have achieved remarkable progress, social
concerns about potential malicious abuse of these technologies bring out an emerging …

The deep image prior showed that a randomly initialized network with a suitable architecture
can be trained to solve inverse imaging problems by simply optimizing it's parameters to …

In recent years there has been significant progress in efficient and lightweight image super-
resolution due in part to the design of several powerful and lightweight attention …

The recently developed transformer networks have achieved impressive performance in
image denoising by exploiting the self-attention (SA) in images. However, the existing …

In single-image super-resolution (SISR) task, it is challenging to recover high-frequency
details from a low-resolution (LR) image due to its ill-posed problem. Most existing CNN …

Among various developments in the field of computer vision, single image super-resolution
of images is one of the most essential tasks. However, compared to the integer magnification …

Open-Set Recognition (OSR) aims to accurately identify known classes while effectively
rejecting unknown classes to guarantee the reliability. Most existing OSR methods focus on …

Dichotomous image segmentation (DIS) has a wide range of real-world applications and
gained increasing research attention in recent years. In this paper, we propose to tackle DIS …

Deep learning methods, in particular, trained convolutional neural networks (CNNs) have
recently been shown to produce compelling results for single image super-resolution (SR) …

In recent years, convolutional neural networks (CNNs) have enabled ubiquitous image
processing applications. As such, CNNs require fast forward propagation runtime to process …