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 …

In recent years, 3D object perception has become a crucial component in the development
of autonomous driving systems, providing essential environmental awareness. However, as …

Existing Visual Object Tracking (VOT) only takes the target area in the first frame as a
template. This causes tracking to inevitably fail in fast-changing and crowded scenes, as it …

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

Real-time perception, or streaming perception, is a crucial aspect of autonomous driving that
has yet to be thoroughly explored in existing research. To address this gap, we present …

Streaming perception, a critical task in computer vision, involves the real-time prediction of
object locations within video sequences based on prior frames. While current methods like …

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 …

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 …

Streaming perception is a crucial task in the field of autonomous driving, which aims to
eliminate the inconsistency between the perception results and the real environment due to …