Video object detection enhances the performance of the still-image based object detection
by exploiting temporal context information from neighboring frames. Most of the state-of-the …

For efficient video object detection, our detector consists of a spatial module and a temporal
module. The spatial module aims to detect objects in static frames using convolutional …

How to exploit spatio-temporal information in video to improve the object detection precision
remains an open problem. In this paper, we boost the object detection accuracy in video with …

Abstract We introduce Spatial-Temporal Memory Networks for video object detection. At its
core, a novel Spatial-Temporal Memory module (STMM) serves as the recurrent …

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 image-based object detectors to the domain of video remains challenging
under resource constraints. Previous efforts utilised optical flow to allow unchanged features …

Object detection in videos is a fundamental technology for applications such as monitoring.
Since video frames are treated as independent input images, static detectors ignore the …

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 …

The deep learning technique has recently led to significant improvement in object detection
accuracy. In many applications, object detection is performed on video data consisting of a …

Recent years have witnessed a trend of applying context frames to boost the performance of
object detection as video object detection. Existing methods usually aggregate features at …