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 …

Extending state-of-the-art object detectors from image to video is challenging. The accuracy
of detection suffers from degenerated object appearances in videos, eg, motion blur, video …

We present a framework for attention-based video object detection using a simple yet
effective external memory management algorithm. An attention mechanism has been …

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 …

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 …

Video object detection is a fundamental and important task in computer vision. One mainstay
solution for this task is to aggregate features from different frames to enhance the detection …

This paper presents the novel idea of generating object proposals by leveraging temporal
information for video object detection. The feature aggregation in modern region-based …

Several existing still image object detectors suffer from image deterioration in videos, such
as motion blur, camera defocus, and partial occlusion. We present DiffusionVID, a diffusion …

Deep convolutional neural networks have achieved great success on various image
recognition tasks. However, it is nontrivial to transfer the existing networks to video due to …

We present an Object-aware Feature Aggregation (OFA) module for video object detection
(VID). Our approach is motivated by the intriguing property that video-level object-aware …