Weakly Supervised Foreground Object Detection Network Using Background Model Image

Weakly Supervised Foreground Object Detection Network Using Background Model Image

In visual surveillance, deep learning-based foreground object detection algorithms are superior to classical background subtraction (BGS)-based algorithms. However, deep learning-based methods are limited because detection performance deteriorates in a new environment different from the training env...

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Bibliographic Details
Main Authors: Jae-Yeul Kim, Jong-Eun Ha
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Visual surveillance
weakly supervised
deep learning
foreground object detection
Online Access:https://ieeexplore.ieee.org/document/9910159/

Internet

https://ieeexplore.ieee.org/document/9910159/

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