Deep learning has become the method of choice to tackle real-world problems in different
domains, partly because of its ability to learn from data and achieve impressive performance …

Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …

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 …

Supervised learning algorithms have shown limited use in the field of anomaly detection due
to the unpredictability and difficulty in acquiring abnormal samples. In recent years …

In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

Abstract Generative Adversarial Network (GAN) is a research hotspot in deep generative
models, which has been widely used in the field of medical image fusion. This paper …

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 …

Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

High-quality, diverse, and photorealistic images can now be generated by unconditional
GANs (eg, StyleGAN). However, limited options exist to control the generation process using …

We describe a simple method for unsupervised domain adaptation, whereby the
discrepancy between the source and target distributions is reduced by swapping the low …