Recently, deep learning has achieved great success in visual tracking. The goal of this
paper is to review the state-of-the-art tracking methods based on deep learning. First, we …

As one of the most comprehensive and objective ways to describe facial expressions, the
Facial Action Coding System (FACS) has recently received significant attention. Over the …

We present YOLO, a new approach to object detection. Prior work on object detection
repurposes classifiers to perform detection. Instead, we frame object detection as a …

Correlation Filter-based trackers have recently achieved excellent performance, showing
great robustness to challenging situations exhibiting motion blur and illumination changes …

Adaptive tracking-by-detection methods are widely used in computer vision for tracking
arbitrary objects. Current approaches treat the tracking problem as a classification task and …

The Jaccard index, also referred to as the intersection-over-union score, is commonly
employed in the evaluation of image segmentation results given its perceptual qualities …

We consider the problem of learning deep neural networks (DNNs) for object category
segmentation, where the goal is to label each pixel in an image as being part of a given …

Edge detection is a critical component of many vision systems, including object detectors
and image segmentation algorithms. Patches of edges exhibit well-known forms of local …

Edge detection is a critical component of many vision systems, including object detectors
and image segmentation algorithms. Patches of edges exhibit well-known forms of local …

Large scale nonlinear support vector machines (SVMs) can be approximated by linear ones
using a suitable feature map. The linear SVMs are in general much faster to learn and …