With the rapid development of Internet technology, the spread of bloody video has become
increasingly serious, causing huge harm to society. In this paper, a bloody video recognition …

Audio-visual video recognition (AVVR) aims to integrate audio and visual clues to categorize
videos accurately. While existing methods train AVVR models using provided datasets and …

High accuracy video label prediction (classification) models are attributed to large scale
data. These data could be frame feature sequences extracted by a pre-trained convolutional …

With the explosive growth of video data in real-world applications, a comprehensive
representation of videos becomes increasingly important. In this paper, we address the …

Instance segmentation of objects is a significant stage in real-time video detection. Object
detection is the task of detecting the information of all types of objects in an image by …

Deep convolutional neural networks (CNNs) are successful in self-extracting features for
video object detection. The deep features and shallow features extracted from CNN are …

Video event recognition plays an important role in the various research fields particularly in
surveillance detection system. In the existing system it is done by deep hierarchical context …

With the exponential growth and availability of sports video data, the need for video analysis
has become crucial. Sports video classification is one of the most challenging problems …

Video is complex due to large variations in motion and rich content in fine-grained visual
details. Abstracting useful information from such information-intensive media requires …

Unconstrained video recognition and Deep Convolution Network (DCN) are two active
topics in computer vision recently. In this work, we apply DCNs as frame-based recognizers …