Deep neural network concepts for background subtraction: A systematic review and comparative evaluation

T Bouwmans, S Javed, M Sultana, SK Jung - Neural Networks, 2019 - Elsevier
Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …

An empirical review of deep learning frameworks for change detection: Model design, experimental frameworks, challenges and research needs

M Mandal, SK Vipparthi - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
Visual change detection, aiming at segmentation of video frames into foreground and
background regions, is one of the elementary tasks in computer vision and video analytics …

BSUV-Net 2.0: Spatio-temporal data augmentations for video-agnostic supervised background subtraction

MO Tezcan, P Ishwar, J Konrad - IEEE Access, 2021 - ieeexplore.ieee.org
Background subtraction (BGS) is a fundamental video processing task which is a key
component of many applications. Deep learning-based supervised algorithms achieve very …

BSUV-Net: A fully-convolutional neural network for background subtraction of unseen videos

O Tezcan, P Ishwar, J Konrad - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
Background subtraction is a basic task in computer vision and video processing often
applied as a pre-processing step for object tracking, people recognition, etc. Recently, a …

Vabus: Edge-cloud real-time video analytics via background understanding and subtraction

H Wang, Q Li, H Sun, Z Chen, Y Hao… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Edge-cloud collaborative video analytics is transforming the way data is being handled,
processed, and transmitted from the ever-growing number of surveillance cameras around …

Background subtraction for moving object detection: explorations of recent developments and challenges

R Kalsotra, S Arora - The Visual Computer, 2022 - Springer
Background subtraction, although being a very well-established field, has required
significant research efforts to tackle unsolved challenges and to accelerate the progress …

A survey of moving object detection methods: A practical perspective

X Zhao, G Wang, Z He, H Jiang - Neurocomputing, 2022 - Elsevier
Moving object detection is the foundation of research in many computer vision fields. In
recent decades, a number of detection methods have been proposed. Relevant surveys …

3DCD: Scene independent end-to-end spatiotemporal feature learning framework for change detection in unseen videos

M Mandal, V Dhar, A Mishra… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Change detection is an elementary task in computer vision and video processing
applications. Recently, a number of supervised methods based on convolutional neural …

Zbs: Zero-shot background subtraction via instance-level background modeling and foreground selection

Y An, X Zhao, T Yu, H Guo, C Zhao… - Proceedings of the …, 2023 - openaccess.thecvf.com
Background subtraction (BGS) aims to extract all moving objects in the video frames to
obtain binary foreground segmentation masks. Deep learning has been widely used in this …

Scene independency matters: An empirical study of scene dependent and scene independent evaluation for CNN-based change detection

M Mandal, SK Vipparthi - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Visual change detection in video is one of the essential tasks in computer vision
applications. Recently, a number of supervised deep learning methods have achieved top …