Multi-exposure image fusion (MEF) is emerging as a research hotspot in the fields of image
processing and computer vision, which can integrate images with multiple exposure levels …

Images captured in low-light environments often suffer from complex degradation. Simply
adjusting light would inevitably result in burst of hidden noise and color distortion. To seek …

Exposure bracketing is crucial to high dynamic range imaging, but it is prone to halos for
static scenes and ghosting artifacts for dynamic scenes. The recently proposed structural …

This paper follows the idea of divide and conquer to propose a multi-exposure fusion
network for the unsupervised generation of high dynamic range-like images. We develop a …

We propose a fast multi-exposure image fusion (MEF) method, namely MEF-Net, for static
image sequences of arbitrary spatial resolution and exposure number. We first feed a low …

Multi-exposure image fusion (MEF) is an important area in computer vision and has attracted
increasing interests in recent years. Apart from conventional algorithms, deep learning …

Convolutional Neural Networks (CNNs) dominate image processing but suffer from local
inductive bias, which is addressed by the transformer framework with its inherent ability to …

The visual system enables humans to perceive all details of the real-world with vivid colors,
while high dynamic range (HDR) technology aims at capturing natural scenes in a closer …

In the animation industry, automatically predicting the quality of cartoon images based on
the inputs of general distortions and color change is an urgent task, while the existing no …

Arbitrary neural style transfer is a vital topic with great research value and wide industrial
application, which strives to render the structure of one image using the style of another …