Deep learning has been extensively applied to segmentation in medical imaging. U‐Net
proposed in 2015 shows the advantages of accurate segmentation of small targets and its …

Histological staining is the gold standard for tissue examination in clinical pathology and life-
science research, which visualizes the tissue and cellular structures using chromatic dyes or …

Image dehazing is a representative low-level vision task that estimates latent haze-free
images from hazy images. In recent years, convolutional neural network-based methods …

Communication systems to date primarily aim at reliably communicating bit sequences.
Such an approach provides efficient engineering designs that are agnostic to the meanings …

Abstract Development of transformer-based text-to-image models is impeded by its slow
generation and complexity, for high-resolution images. In this work, we put forward a …

Measuring the perception of visual content is a long-standing problem in computer vision.
Many mathematical models have been developed to evaluate the look or quality of an …

Neural radiance fields (NeRF) have shown great success in modeling 3D scenes and
synthesizing novel-view images. However, most previous NeRF methods take much time to …

The advancement of real-time 3D scene reconstruction and novel view synthesis has been
significantly propelled by 3D Gaussian Splatting (3DGS). However, effectively training large …

Recently, learned image compression techniques have achieved remarkable performance,
even surpassing the best manually designed lossy image coders. They are promising to be …

Neural Radiance Fields (NeRF) are able to reconstruct scenes with unprecedented fidelity,
and various recent works have extended NeRF to handle dynamic scenes. A common …