Deep neural network concepts for background subtraction: A systematic review and comparative evaluation
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 …
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 …
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
Background subtraction (BGS) is a fundamental video processing task which is a key
component of many applications. Deep learning-based supervised algorithms achieve very …
component of many applications. Deep learning-based supervised algorithms achieve very …
BSUV-Net: A fully-convolutional neural network for background subtraction of unseen videos
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 …
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
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 …
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 …
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 …
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
Change detection is an elementary task in computer vision and video processing
applications. Recently, a number of supervised methods based on convolutional neural …
applications. Recently, a number of supervised methods based on convolutional neural …
Zbs: Zero-shot background subtraction via instance-level background modeling and foreground selection
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 …
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 …
applications. Recently, a number of supervised deep learning methods have achieved top …