Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …

Video objection detection is a challenging task because isolated video frames may
encounter appearance deterioration, which introduces great confusion for detection. One of …

For autonomous driving, perception is a primary and essential element that fundamentally
deals with the insight into the ego vehicle's environment through sensors. Perception is …

In this work, we introduce a Denser Feature Network (DenserNet) for visual localization. Our
work provides three principal contributions. First, we develop a convolutional neural network …

As self-driving or autonomous vehicles proliferate in our society, there is a need for their
computing vision systems to be able to identify objects accurately, no matter the weather …

Despite significant progress in vision-based detection methods, the task of detecting traffic
objects in foggy weather remains challenging. The presence of fog reduces visibility, which …

Storm prediction provides the early alert for preparation, avoiding potential damage to
property and human safety. However, a traditional storm prediction model usually incurs …

Video object detection needs to solve feature degradation situations that rarely happen in
the image domain. One solution is to use the temporal information and fuse the features from …

Multi-object tracking and segmentation (MOTS) is a critical task for autonomous driving
applications. The existing MOTS studies face two critical challenges: 1) the published …

The advancement of computer vision has pushed visual analysis tasks from still images to
the video domain. In recent years, video instance segmentation, which aims at tracking and …