While the Internet of Things (IoT) devices, such as smartwatches, provide a range of services
from managing financial transactions to monitoring smart homes, these devices often lead to …

In this paper, we present a survey on pattern recognition applications of Support Vector
Machines (SVMs). Since SVMs show good generalization performance on many real-life …

Abstract 3D Morphable Model (3DMM) is a statistical model of facial shape and texture using
a set of linear basis functions. Most of the recent 3D face reconstruction methods aim to …

Unsupervised anomaly detection in videos is a challenging task owing to the remarkable
generalization capacity of the deep convolutional autoencoders and the complex nature of …

Video Anomaly Detection (VAD) has been traditionally tackled in two main methodologies:
the reconstruction-based approach and the prediction-based one. As the reconstruction …

Conventional methods for object detection usually require substantial amounts of training
data and annotated bounding boxes. If there are only a few training data and annotations …

Human activity recognition in videos has been widely studied and has recently gained
significant advances with deep learning approaches; however, it remains a challenging task …

In this paper, we propose a novel method to precisely match two aerial images that were
obtained in different environments via a two-stream deep network. By internally augmenting …

Temporal action localization (TAL) is a task of identifying a set of actions in a video, which
involves localizing the start and end frames and classifying each action instance. Existing …

Although many approaches for multi-human pose estimation in videos have shown profound
results, they require densely annotated data which entails excessive man labor …