Recent approaches have achieved great success on still image object detection. Despite the
high accuracy, directly applying image object detectors for video object detection is rather …

To deal with the challenges in video object detection (VOD), such as occlusion and motion
blur, many state-of-the-art video object detectors adopt a feature aggregation module to …

While single-image object detectors can be naively applied to videos in a frame-by-frame
fashion, the prediction is often temporally inconsistent. Moreover, the computation can be …

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 …

The deep learning technique has recently led to significant improvement in object-detection
accuracy. Numerous object detection schemes have been designed to process each frame …

Video object detection aims to detect and track each object in a given video. However, due
to the problem of appearance deterioration in the video, it is still challenging to obtain good …

In recent years, the excellent image-based object detection algorithms are transferred to the
video object detection directly. These frame-by-frame processing methods are suboptimal …

Object detection in still images has been extensively investigated recent years. But object
detection in videos is still a challenging research topic. Directly using those methods for still …

Video object detection is a fundamental problem in computer vision and has a wide
spectrum of applications. Based on deep networks, video object detection is actively studied …

As a basic research topic of computer vision, object detection is facing the challenges of
being extended for video object detection. For deformation anomaly, low-quality candidate …