Video object detection task is challenging due to the nonrigid and rigid appearance
deformations in videos. Most of the typical competitive methods are to enhance per-frame …

Video object detection is a challenging problem in computer vision. In this paper, we
propose a novel spatial-temporal feature aggregation network to deal with this issue …

Recent progress in video object detection (VOD) has shown that aggregating features from
other frames to capture long-range contextual information is very important to deal with the …

Aggregating temporal features from other frames is verified to be very effective for video
object detection to overcome the challenges in still images, such as occlusion, motion blur …

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 …

Video object detection is a challenging task due to the presence of appearance deterioration
in video frames. Recently, feature aggregation based methods which aggregate context …

Video object detection task has received extensive research attention and various methods
have been proposed. The quality of single frame in the original video is usually deteriorated …

Video object detection is a challenging task due to deteriorated object appearances. To
enhance per-frame features, one way is to aggregate features from several support frames …

In recent years, outstanding image-based object detectors were extended for video object
detection. Such extension requires to address two challenging problems in videos, namely …

How do humans recognize an object in a piece of video? Due to the deteriorated quality of
single frame, it may be hard for people to identify an occluded object in this frame by just …