Over the past years, numerous methods have emerged to automate the quantification of
animal behavior at a resolution not previously imaginable. This has opened up a new field of …

This article is a survey of deep learning methods for single and multiple sound source
localization, with a focus on sound source localization in indoor environments, where …

Abstract Multiple Object Tracking (MOT) has emerged as a hot issue in the field of computer
vision recently. MOT has academic and commercial potential in urban public security …

Despite considerable similarities between multiple object tracking (MOT) and single object
tracking (SOT) tasks, modern MOT methods have not benefited from the development of …

The recent trend in multiple object tracking (MOT) is heading towards leveraging deep
learning to boost the tracking performance. However, it is not trivial to solve the data …

Occlusion between different objects is a typical challenge in Multi-Object Tracking (MOT),
which often leads to inferior tracking results due to the missing detected objects. The …

Modern multi-object tracking (MOT) systems usually build trajectories through associating
per-frame detections. However, facing the challenges of camera motion, fast motion, and …

Despite the recent advances in multiple object tracking (MOT), achieved by joint detection
and tracking, dealing with long occlusions remains a challenge. This is due to the fact that …

Transformers have proven superior performance for a wide variety of tasks since they were
introduced. In recent years, they have drawn attention from the vision community in tasks …

Autonomous systems that operate in dynamic environments require robust object tracking in
3D as one of their key components. Most recent approaches for 3D multi-object tracking …