Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …

Particle tracking is a fundamental technique for investigating a variety of biophysical
processes, from intracellular dynamics to the characterization of cell motility and migration …

Recently, Multi-Object Tracking (MOT) has attracted rising attention, and accordingly,
remarkable progresses have been achieved. However, the existing methods tend to use …

The goal of multi-object tracking (MOT) is detecting and tracking all the objects in a scene,
while keeping a unique identifier for each object. In this paper, we present a new robust …

Tracking has traditionally been the art of following interest points through space and time.
This changed with the rise of powerful deep networks. Nowadays, tracking is dominated by …

Numerous learning-based approaches to single image deblurring for camera and object
motion blurs have recently been proposed. To generalize such approaches to real-world …

The problem of tracking multiple objects in a video sequence poses several challenging
tasks. For tracking-by-detection, these include object re-identification, motion prediction and …

With rapid progress and significant successes in a wide spectrum of applications, deep
learning is being applied in many safety-critical environments. However, deep neural …

In this work, we focus on improving online multi-object tracking (MOT). In particular, we
propose a novel region-based Siamese Multi-Object Tracking network, which we name …

An essential step toward understanding brain function is to establish a structural framework
with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and …