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 …

Edge-cloud collaborative video analytics is transforming the way data is being handled,
processed, and transmitted from the ever-growing number of surveillance cameras around …

Transferring image-based object detectors to the domain of videos remains a challenging
problem. Previous efforts mostly exploit optical flow to propagate features across frames …

Single shot detectors that are potentially faster and simpler than two-stage detectors tend to
be more applicable to object detection in videos. Nevertheless, the extension of such object …

We present FlexPatch, a novel mobile system to enable accurate and real-time object
detection over high-resolution video streams. A widely-used approach for real-time video …

This paper proposes an end-to-end deep learning framework, termed as motion-aid feature
calibration network (MFCN), for video object detection. The key idea is to leverage on the …

Video object detection (VOD) focuses on detecting objects for each frame in a video, which
is a challenging task due to appearance deterioration in certain video frames. Recent works …

We present a video representation learning framework for real-time video object detection.
Our approach is based on the interesting observation that a powerful prior knowledge of …

Real-time mobile video analysis like object detection and tracking is key to various
household applications such as AR, cognitive assistance and smart home. Such …

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 …