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 …

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 …

There has been significant progresses for image object detection recently. Nevertheless,
video object detection has received little attention, although it is more challenging and more …

Video object detection is challenging because objects that are easily detected in one frame
may be difficult to detect in another frame within the same clip. Recently, there have been …

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 …

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 yet challenging task in computer vision. One
practical solution is to take advantage of temporal information from the video and apply …

Single-frame object detectors perform well on videos sometimes, even without temporal
context. However, challenges such as occlusion, motion blur, and rare poses of objects are …

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

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 …