Generative Adversarial Networks (GANs) have been very successful for synthesizing the
images in a given dataset. The artificially generated images by GANs are very realistic. The …

Medical image fusion can provide doctors with more detailed data and thus improve the
accuracy of disease diagnosis. In recent years, deep learning has been widely used in the …

The objective of person re-identification (Re-ID) is to match unmistakable people across
different settings and camera views. Although the use of convolutional neural networks …

We present EXE-GAN, a novel exemplar-guided facial inpainting framework using
generative adversarial networks. Our approach not only preserves the quality of the input …

Image inpainting is currently a hot topic within the field of computer vision. It offers a viable
solution for various applications, including photographic restoration, video editing, and …

Image inpainting aims to restore visually realistic contents from a corrupted image, while
inpainting forensic methods focus on locating the inpainted regions to fight against …

Weakly supervised object localization (WSOL) is both a promising and challenging task that
aims to achieve object localization exclusively through image category labels for …

Due to the influence of the light source environment during image acquisition or the subject
not fully opening their eyes, there are phenomena such as light spot interference, eyelash or …

The deep rectangling task aims to transform edge-irregular stitched images into
standardised rectangular formats using deep learning. Existing deep rectangling solutions …

Deep learning has enabled image style transfer to make great strides forward. However,
unlike many other styles, transferring the watercolor style to portraits is significantly …