Object detection is one of the most important tasks of computer vision. It is usually performed
by evaluating a subset of the possible locations of an image, that are more likely to contain …

Object detection in videos is an important task in computer vision for various applications
such as object tracking, video summarization and video search. Although great progress has …

Recent outstanding results of supervised object detection in competitions and challenges
are often associated with specific metrics and datasets. The evaluation of such methods …

We propose a novel approach to boost the performance of generic object detectors on
videos by learning videospecific features using a deep neural network. The insight behind …

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 …

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 …

Detecting objects in a video is a compute-intensive task. In this paper we propose CaTDet, a
system to speedup object detection by leveraging the temporal correlation in video. CaTDet …

This paper presents a cascaded regional spatiotemporal feature-routing networks for video
object detection. Region proposal networks in faster region-based convolutional neural …

Abstract We propose a Spatiotemporal Sampling Network (STSN) that uses deformable
convolutions across time for object detection in videos. Our STSN performs object detection …

Object detection is one of the most important topics in computer vision task and has obtained
impressive performance thanks to the use of deep convolutional neural network. For object …