Recent object detection studies have been focused on video sequences, mostly due to the
increasing demand of industrial applications. Although single-image architectures achieve …

Video object detection is a challenging task because of the presence of appearance
deterioration in certain video frames. One typical solution is to aggregate neighboring …

State-of-the-art video object detection methods maintain a memory structure, either a sliding
window or a memory queue, to enhance the current frame using attention mechanisms …

With the rapid development of Industrial Internet of Things (IIoT) technology, video
surveillance devices and video data in IIoT environments are massively growing and …

Video object detection has attracted increasing attention in recent years. Although great
success has been achieved by off-the-shelf video object detection methods through …

Despite significant progress in semi-supervised learning for image object detection, several
key issues are yet to be addressed for video object detection:(1) Achieving good …

Deep learning models have significantly improved object detection, which is essential for
visual sensing. However, their increasing complexity results in higher latency and resource …

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

Transferring existing image-based detectors to the video is non-trivial since the quality of
frames is always deteriorated by part occlusion, rare pose, and motion blur. Previous …

Video object detection is a fundamental research task for scene understanding. Compared
with object detection in images, object detection in videos has been less researched due to …