Many image processing, computer graphics, and computer vision problems can be treated
as image-to-image translation tasks. Such translation entails learning to map one visual …

As the scale and complexity of networks grow rapidly, management, maintenance, and
optimization of them are becoming increasingly challenging tasks for network administrators …

Important information that relates to a specific topic in a document is often organized in
tabular format to assist readers with information retrieval and comparison, which may be …

Image-to-image translation is to learn a mapping between images from a source domain
and images from a target domain. In this paper, we introduce the attention mechanism …

Domain adaptation person re-identification (Re-ID) is a challenging task, which aims to
transfer the knowledge learned from the labeled source domain to the unlabeled target …

The goal of unpaired image-to-image translation is to learn a mapping from a source domain
to a target domain without using any labeled examples of paired images. This problem can …

Image-to-Image (I2I) translation is an emerging topic in academia, and it also has been
applied in real-world industry for tasks like image synthesis, super-resolution, and …

The unpaired image-to-image translation aims to translate input images from one source
domain to some desired outputs in a target domain by learning from unpaired training data …

Brain magnetic resonance imaging segmentation is a recent and still popular research area.
Good and accurate segmentation results play an important role in the diagnosis of cancer or …

Previous works on generative adversarial networks (GANs) mainly focus on how to
synthesize high-fidelity images. In this paper, we present a framework to leverage the …