Convolutional neural network (CNN) and Transformer have achieved great success in
multimedia applications. However, little effort has been made to effectively and efficiently …

Recent person Re-IDentification (ReID) systems have been challenged by changes in
personnel clothing, leading to the study of Cloth-Changing person ReID (CC-ReID) …

Abstract Unsupervised Domain Adaptation (UDA) aims to adapt models from labeled source
domains to unlabeled target domains. When adapting to adverse scenes, existing UDA …

Multi-view action recognition aims to identify action categories from given clues. Existing
studies ignore the negative influences of fuzzy views between view and action in …

Images captured in low-light or underwater environments are often accompanied by
significant degradation, which can negatively impact the quality and performance of …

Not all semantics become confusing when deploying a semantic segmentation model for
real-world scene understanding of adverse weather. The true semantics of most pixels have …

Domain adaptation is commonly employed in crowd counting to bridge the domain gaps
between different datasets. However, existing domain adaptation methods tend to focus on …

Adverse weather conditions such as haze and snowfall can degrade the quality of captured
images and affect performance of drone detection. Therefore, it is challenging to locate and …

Deep learning improves the performance of crowd counting, but model migration remains a
tricky challenge. Due to the reliance on training data and inherent domain shift, model …

The wavelet transform has emerged as a powerful tool in deciphering structural information
within images. And now, the latest research suggests that combining the prowess of wavelet …