As a common image editing operation, image composition aims to combine the foreground
from one image and another background image, resulting in a composite image. However …

Recent works on image harmonization solve the problem as a pixel-wise image translation
task via large autoencoders. They have unsatisfactory performances and slow inference …

In this paper, we present PCT-Net, a simple and general image harmonization method that
can be easily applied to images at full resolution. The key idea is to learn a parameter …

Image inpainting aims to fill the missing hole of the input. It is hard to solve this task
efficiently when facing high-resolution images due to two reasons:(1) Large reception field …

Learning-based image harmonization techniques are usually trained to undo synthetic
global transformations, applied to a masked foreground in a single ground truth photo. This …

Shadows often occur when we capture the document with casual equipment, which
influences the visual quality and readability of the digital copies. Different from the …

The goal of image harmonization is adjusting the foreground appearance in a composite
image to make the whole image harmonious. To construct paired training images, existing …

Image harmonization is a critical task in computer vision, which aims to adjust the
foreground to make it compatible with the background. Recent works mainly focus on using …

We present a simple yet effective self-supervised pretraining method for image
harmonization which can leverage large-scale unannotated image datasets. To achieve this …

Harmonizing cut-and-paste images into perceptually realistic ones is challenging, as it
requires a full understanding of the discrepancies between the background of the target …