Contrastive language-image pretraining (CLIP) has demonstrated remarkable success in
various image tasks. However, how to extend CLIP with effective temporal modeling is still …

The current 3D human pose estimators face challenges in adapting to new datasets due to
the scarcity of 2D-3D pose pairs in target domain training sets. We present the Multi …

Human pose estimation is a challenging task due to its structured data sequence nature.
Existing methods primarily focus on pair-wise interaction of body joints, which is insufficient …

Anomaly segmentation plays a crucial role in identifying anomalous objects within images,
which facilitates the detection of road anomalies for autonomous driving. Although existing …

Abstract The Intelligent and Connected Vehicle Cloud Control System is a critical approach
for achieving high-level autonomous driving. One of the key challenges at the perception …

With over 1.6 million traffic deaths in 2016, automated vehicles equipped with automated
driving systems (ADSs) have the potential to increase traffic safety by assuming human …

Video prediction is a pixel-level task that generates future frames by employing the historical
frames. There often exist continuous complex motions, such as object overlapping and …

The decision-making performance of autonomous vehicles tends to be unstable at
unsignalized intersections, making it difficult for them to make optimal decisions. We …

Transformer architecture has demonstrated significant potential in hyperspectral object
tracking by leveraging global correlation learning to accurately represent the data …

In the realm of facial analysis, accurate landmark detection is crucial for various applications,
ranging from face recognition and expression analysis to animation. Conventional heatmap …