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 …

The goal of this paper is to review the state-of-the-art progress on visual tracking methods,
classify them into different categories, as well as identify future trends. Visual tracking is a …

We tackle the task of semi-supervised video object segmentation, ie segmenting the pixels
belonging to an object in the video using the ground truth pixel mask for the first frame. We …

Face detection is one of the most studied topics in computer vision literature, not only
because of the challenging nature of face as an object, but also due to the countless …

This paper investigates long-term tracking of unknown objects in a video stream. The object
is defined by its location and extent in a single frame. In every frame that follows, the task is …

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with
each incoming frame and the information provided up to the moment. It still remains a …

Sparse representation has been applied to visual tracking by finding the best candidate with
minimal reconstruction error using target templates. However most sparse representation …

Visual object tracking is a significant computer vision task which can be applied to many
domains, such as visual surveillance, human computer interaction, and video compression …

In this paper, we address the problem of tracking an object in a video given its location in the
first frame and no other information. Recently, a class of tracking techniques called “tracking …

This study presents an implementation of a Machine Learning model to predict customer
loyalty for a financial company. We compare the accuracy of two Gradient Boosting Decision …