Recent text-to-image (T2I) diffusion models have achieved remarkable progress in
generating high-quality images given text-prompts as input. However, these models fail to …

Abstract Weakly-supervised Video Anomaly Detection (wVAD) aims to detect frame-level
anomalies using only video-level labels in training. Due to the limitation of coarse-grained …

Previous work has shown that CNN-based local distribution learning can efficiently
reconstruct high-resolution images, but with limited performance improvement against …

Graph learning is widely applied to process various complex data structures (eg, time series)
in different domains. Due to multidimensional observations and the requirement for accurate …

Recent advances in pre-trained vision-language models have successfully boosted the
performance of unsupervised image representation in many vision tasks. Most of existing …

Multi-label learning (MLL) can be viewed as an extension of multi-class learning (MCL) that
supports nonexclusive labels. Random k-labelset ensemble (RAkEL) is a popular algorithm …

Planning wireless network coverage is essential for assessing network performance and
strategizing future deployments. Traditionally, this process has been complex, demanding …