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 …

Recently, one-stage detectors have achieved competitive accuracy and faster speed
compared with traditional two-stage detectors on image data. However, in the field of video …

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 …

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 …

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 …

Video object detection is a tough task due to the deteriorated quality of video sequences
captured under complex environments. Currently, this area is dominated by a series of …

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 …

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 …