Video objection detection is challenging in the presence of appearance deterioration in
certain video frames. One of typical solutions is to enhance per-frame features through …

With a single eye fixation lasting a fraction of a second, the human visual system is capable
of forming a rich representation of a complex environment, reaching a holistic understanding …

Temporal object detection has attracted significant attention, but most popular detection
methods cannot leverage rich temporal information in videos. Very recently, many …

Video object detection is challenging in the presence of appearance deterioration in certain
video frames. Therefore, it is a natural choice to aggregate temporal information from other …

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 …

Given the vast amounts of video available online, and recent breakthroughs in object
detection with static images, object detection in video offers a promising new frontier …

Although there are well established object detection methods based on static images, their
application to video data on a frame by frame basis faces two shortcomings:(i) lack of …

In this paper, we investigate a weakly-supervised object detection framework. Most existing
frameworks focus on using static images to learn object detectors. However, these detectors …

Video object detection (VID) is challenging because of the high variation of object
appearance as well as the diverse deterioration in some frames. On the positive side, the …

High-performance object detection relies on expensive convolutional networks to compute
features, often leading to significant challenges in applications, eg those that re-quire …