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 …
Y Dai, Z Hu, S Zhang, L Liu - Displays, 2022 - Elsevier
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 …
P Dai, R Weng, W Choi, C Zhang… - Proceedings of the …, 2021 - openaccess.thecvf.com
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 …
S Han, P Huang, H Wang, E Yu, D Liu, X Pan - Neurocomputing, 2022 - Elsevier
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 …
Y Xu, Y Ban, G Delorme, C Gan, D Rus… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
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 …