While it is nearly effortless for humans to quickly assess the perceptual similarity between
two images, the underlying processes are thought to be quite complex. Despite this, the …

Automatically learned quality assessment for images has recently become a hot topic due to
its usefulness in a wide variety of applications, such as evaluating image capture pipelines …

We study the problem of photo cropping, which aims to find a cropping window of an input
image to preserve as much as possible its important parts while being aesthetically …

Learning-based color enhancement approaches typically learn to map from input images to
retouched images. Most of existing methods require expensive pairs of input-retouched …

Recently, product images have gained increasing attention in clothing recommendation
since the visual appearance of clothing products has a significant impact on consumers» …

Facial beauty prediction (FBP) is a significant visual recognition problem to make
assessment of facial attractiveness that is consistent to human perception. To tackle this …

Image cropping aims at improving the aesthetic quality of images by adjusting their
composition. Most weakly supervised cropping methods (without bounding box supervision) …

Aggregation structures with explicit information, such as image attributes and scene
semantics, are effective and popular for intelligent systems for assessing aesthetics of visual …

A key problem in blind image quality assessment (BIQA) is how to effectively model the
properties of human visual system in a data-driven manner. In this paper, we propose a …

We introduce EnhanceGAN, an adversarial learning based model that performs automatic
image enhancement. Traditional image enhancement frameworks typically involve training …