In the realm of medical imaging, distinct magnetic resonance imaging (MRI) modalities can
provide complementary medical insights. However, it is not uncommon for one or more …

Neural implicit functions have demonstrated significant importance in various areas such as
computer vision, graphics. Their advantages include the ability to represent complex shapes …

We propose Stratified Image Transformer (StraIT), a pure non-autoregressive (NAR)
generative model that demonstrates superiority in high-quality image synthesis over existing …

Vision foundation models exhibit impressive power, benefiting from the extremely large
model capacity and broad training data. However, in practice, downstream scenarios may …

Media narratives in environmental communication often broadcast scientific and complex
information from the perspective of professional experts, and while focusing on emotions …

The tokenizer, as one of the fundamental components of large models, has long been
overlooked or even misunderstood in visual tasks. One key factor of the great …

Most video restoration networks are slow, have high computational load, and can't be used
for real-time video enhancement. In this work, we design an efficient and fast framework to …

Predicting the binding affinity between a T cell receptor (TCR) and an epitope is essential in
cancer immunotherapy. The existing predictor epiTCR employs Random Forest to …

Skin cancer has risen to be one of the significant forms of cancer worldwide. However, the
traditional means of skin cancer detection requires manual examination by an expert, which …

Deep learning has achieved tremendous success on various computer vision tasks.
However, deep learning methods and models are usually computationally expensive …