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 …

Recent advances in deep learning have shown exciting promise in filling large holes in
natural images with semantically plausible and context aware details, impacting …

The breakthrough brought by generative adversarial networks (GANs) in computer vision
(CV) applications has gained a lot of attention in different fields due to their ability to capture …

Remote-sensing (RS) Change Detection (CD) aims to detect" changes of interest" from co-
registered bi-temporal images. The performance of existing deep supervised CD methods is …

In this paper, we attack a few-shot open-set recognition (FSOSR) problem, which is a
combination of few-shot learning (FSL) and open-set recognition (OSR). It aims to quickly …

We present a simple yet effective self-supervised framework for audio-visual representation
learning, to localize the sound source in videos. To understand what enables to learn useful …

Deep learning has shown its effectiveness in histopathology image analysis, such as
pathology detection and classification. However, stain colour variation in Hematoxylin and …

Conditional score-based diffusion model (SBDM) is for conditional generation of target data
with paired data as condition, and has achieved great success in image translation …

Unpaired image-to-image translation (I2I) is an ill-posed problem, as an infinite number of
translation functions can map the source domain distribution to the target distribution …

Near infrared spectroscopy (NIR) provides rich information in agricultural operations and
experiments to determine crop parameters which are not visible to the human eye …