Background subtraction methods are widely exploited for moving object detection in videos
in many applications, such as traffic monitoring, human motion capture, and video …

To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a
new pair of precision-recall measures of performance that treats errors of all types uniformly …

There is a large variety of trackers, which have been proposed in the literature during the
last two decades with some mixed success. Object tracking in realistic scenarios is a difficult …

Video-surveillance and traffic analysis systems can be heavily improved using vision-based
techniques able to extract, manage and track objects in the scene. However, problems arise …

Moving shadows need careful consideration in the development of robust dynamic scene
analysis systems. Moving shadow detection is critical for accurate object detection in video …

Transformer-based architectures represent the state of the art in sequence modeling tasks
like machine translation and language understanding. Their applicability to multi-modal …

Connecting Vision and Language plays an essential role in Generative Intelligence. For this
reason, large research efforts have been devoted to image captioning, ie describing images …

Data-driven saliency has recently gained a lot of attention thanks to the use of convolutional
neural networks for predicting gaze fixations. In this paper, we go beyond standard …

The paper presents an approach for detecting vehicles in urban traffic scenes by means of
rule-based reasoning on visual data. The strength of the approach is its formal separation …

Novelty detection is commonly referred as the discrimination of observations that do not
conform to a learned model of regularity. Despite its importance in different application settings, …