With image object detection techniques progressing, video object detection attracts a lot of
attention more than ever before. However, the performance of detecting the object from a …

With the proposal of edge computing, lots of intelligence applications have made significant
progress. For enormous video analysis, how to further accelerate the process is still a major …

Video object detection has drawn more and more attention in recent years. Compared with
object detection from image, object detection in video is more useful in many practical …

The existing methods for video object detection mainly depend on two-stage image object
detectors. The fact that two-stage detectors are generally slow makes it difficult to apply in …

Video small object detection is a difficult task due to the lack of object information. Recent
methods focus on adding more temporal information to obtain more potent high-level …

One of the major challenges in video object detection is drastic scale changes of objects due
to camera motion. In this paper, we propose a two-path Convolutional Long Short-Term …

Compared with object detection in static images, object detection in videos is more
challenging due to degraded image qualities. An effective way to address this problem is to …

Several existing still image object detectors suffer from image deterioration in videos, such
as motion blur, camera defocus, and partial occlusion. We present DiffusionVID, a diffusion …

Video object detection has been an important yet challenging topic in computer vision.
Traditional methods mainly focus on designing the image-level or box-level feature …

Video object detection, a basic task in the computer vision field, is rapidly evolving and
widely used. In recent years, deep learning methods have rapidly become widespread in the …