Abstract The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-
term single-object visual trackers that do not apply pre-learned models of object …

We present a novel framework for hallucinating faces of unconstrained poses and with very
low resolution (face size as small as 5pxIOD). In contrast to existing studies that mostly …

The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object
visual trackers that do not apply pre-learned models of object appearance. Results of 70 …

Recently, technologies such as face detection, facial landmark localisation and face
recognition and verification have matured enough to provide effective and efficient solutions …

In this paper, we introduce the so-called DEEP-SEE framework that jointly exploits computer
vision algorithms and deep convolutional neural networks (CNNs) to detect, track and …

This paper introduces a novel real-time algorithm for facial landmark tracking. Compared to
detection, tracking has both additional challenges and opportunities. Arguably the most …

In this paper, we propose a novel event-triggered tracking framework for fast and robust
visual tracking in the presence of model drift and occlusion. The resulting tracker not only …

Most existing part-based tracking methods are part-to-part trackers, which usually have two
separated steps including the part matching and target localization. Different from existing …

Linear regression is a fundamental building block in many face detection and tracking
algorithms, typically used to predict shape displacements from image features through a …

The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object
visual trackers that do not apply pre-learned models of object appearance. Results of 70 …