Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

In image-to-image translation, each patch in the output should reflect the content of the
corresponding patch in the input, independent of domain. We propose a straightforward …

Score-based diffusion models (SBDMs) have achieved the SOTA FID results in unpaired
image-to-image translation (I2I). However, we notice that existing methods totally ignore the …

Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …

Perceiving the similarity between images has been a long-standing and fundamental
problem underlying various visual generation tasks. Predominant approaches measure the …

Recently, contrastive learning-based image translation methods have been proposed, which
contrasts different spatial locations to enhance the spatial correspondence. However, the …

Histological artefacts in cryosectioned tissue can hinder rapid diagnostic assessments
during surgery. Formalin-fixed and paraffin-embedded (FFPE) tissue provides higher quality …

We propose a novel spatially-correlative loss that is simple, efficient, and yet effective for
preserving scene structure consistency while supporting large appearance changes during …

Unsupervised image-to-image translation is a central task in computer vision. Current
translation frameworks will abandon the discriminator once the training process is …