awesome-background-subtraction
github.com/murari023/awesome-background-subtraction ↗A curated list of background subtraction related papers and resources
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me landmark papers in background subtraction resources from awesome-background-subtraction"
Installation instructions →What's inside
Non-Deep Learning based Papers
- 1999 - Adaptive background mixture models for real-time trackingLandmark Papers in Background Subtraction
Adaptive background mixture models for real-time tracking
- 2006 - A Texture-Based Method for Modeling the Background and Detecting Moving ObjectsLandmark Papers in Background Subtraction
A Texture-Based Method for Modeling the Background and Detecting Moving Objects
- 2011 - ViBe: A Universal Background Subtraction Algorithm for Video SequencesLandmark Papers in Background Subtraction
ViBe: A Universal Background Subtraction Algorithm for Video Sequences
- 2012 - PBAS - Background Segmentation with Feedback: The Pixel-Based Adaptive SegmenterLandmark Papers in Background Subtraction
PBAS - Background Segmentation with Feedback: The Pixel-Based Adaptive Segmenter
- 2015 - SuBSENSE - A Universal Change Detection Method With Local Adaptive SensitivityLandmark Papers in Background Subtraction
SuBSENSE - A Universal Change Detection Method With Local Adaptive Sensitivity
- 2018 - A Background Modeling and Foreground Detection Algorithm Using Scaling Coefficients Defined With a Color Model Called Lightness-Red-Green-Blue2018 Papers
A Background Modeling and Foreground Detection Algorithm Using Scaling Coefficients Defined With a Color Model Called Lightness-Red-Green-Blue
Review/survey Papers
- 2014 - Traditional and recent approaches in background modeling for foreground detection: An overview
Traditional and recent approaches in background modeling for foreground detection: An overview
- 2018 - New trend in video foreground detection using deep learning
New trend in video foreground detection using deep learning
- 2019 - Background Subtraction in Real Applications: Challenges, Current Models and Future Directions
Background Subtraction in Real Applications: Challenges, Current Models and Future Directions
- 2021 - An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs
An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs
2016 Papers
- 2016 - Deep Background Subtraction with Scene-Specific Convolutional Neural Networks
Deep Background Subtraction with Scene-Specific Convolutional Neural Networks
2017 Papers
- 2017 - A Deep Convolutional Neural Network for Background Subtraction
A Deep Convolutional Neural Network for Background Subtraction
- 2017 - Analytics of deep neural network in change detection
Analytics of deep neural network in change detection
- 2017 - Background modelling based on generative unet
Background modelling based on generative unet
- 2017 - Background subtraction using encoder-decoder structured convolutional neural network
Background subtraction using encoder-decoder structured convolutional neural network
- 2017 - End-to-end video background subtraction with 3D convolutional neural networks
End-to-end video background subtraction with 3D convolutional neural networks
- 2017 - Foreground Segmentation for Anomaly Detection in Surveillance Videos Using Deep Residual Networks
Foreground Segmentation for Anomaly Detection in Surveillance Videos Using Deep Residual Networks
2018 Papers
- 2018 - A 3D Atrous Convolutional Long Short-Term Memory Network for Background SubtractionJournals
A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction
- 2018 - A Co-occurrence Background Model with Hypothesis on Degradation Modification for Object Detection in Strong Background ChangesConference
A Co-occurrence Background Model with Hypothesis on Degradation Modification for Object Detection in Strong Background Changes
- 2018 - A Foreground Inference Network for Video Surveillance Using Multi-View Receptive FieldJournals
A Foreground Inference Network for Video Surveillance Using Multi-View Receptive Field
- 2018 - A novel framework for background subtraction and foreground detectionJournals
A novel framework for background subtraction and foreground detection
- 2018 - Background Subtraction via 3D Convolutional Neural NetworksConference
Background Subtraction via 3D Convolutional Neural Networks
- 2018 - BSCGAN: Deep Background Subtraction with Conditional Generative Adversarial Networks
BSCGAN: Deep Background Subtraction with Conditional Generative Adversarial Networks
2019 Papers
- 2019 - 3DFR: A Swift 3D Feature Reductionist Framework for Scene Independent Change DetectionJournals
IEEE Signal Processing Letters
- 2019 - A 3D CNN-LSTM-Based Image-to-Image Foreground SegmentationJournals
IEEE Transactions on Intelligent Transportation Systems
- 2019 - An end-to-end deep learning approach for simultaneous background modeling and subtractionConferences
An end-to-end deep learning approach for simultaneous background modeling and subtraction
- 2019 - Combining Background Subtraction Algorithms with Convolutional Neural NetworkJournals
Journal of Electronic Imaging
- 2019 - Deep neural network concepts for background subtraction: A systematic review and comparative evaluationJournals
Neural Networks, Elsevier
- 2019 - DeepPBM: Deep Probabilistic Background Model Estimation from Video SequencesJournals
Arxiv
2020 Papers
- 2020 - 3DCD: A Scene Independent End-to-End Spatiotemporal Feature Learning Framework for Change Detection in Unseen Videos
IEEE Transactions on Image Processing
- 2020 - An End-to-End Edge Aggregation Network for Moving Object Segmentation
An End-to-End Edge Aggregation Network for Moving Object Segmentation
- 2020 - BSUV-Net: A Fully-Convolutional Neural Network for Background Subtraction of Unseen Videos
BSUV-Net: A Fully-Convolutional Neural Network for Background Subtraction of Unseen Videos
- 2020 - Graph Moving Object Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
- 2020 - MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos
MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos
- 2020 - MotionRec: Unified Deep Framework for Moving Object Recognition
MotionRec: Unified Deep Framework for Moving Object Recognition
2021 Papers
- 2021 - BSUV-Net 2.0: Spatio-Temporal Data Augmentations for Video-Agnostic Supervised Background Subtraction
BSUV-Net 2.0: Spatio-Temporal Data Augmentations for Video-Agnostic Supervised Background Subtraction
- 2021 - Deep Adversarial Network for Scene Independent Moving Object Segmentation
Deep Adversarial Network for Scene Independent Moving Object Segmentation
- 2021 - End-to-End Recurrent Generative Adversarial Network for Traffic and Surveillance Applications
End-to-End Recurrent Generative Adversarial Network for Traffic and Surveillance Applications
- 2021 - Multi-Frame Recurrent Adversarial Network for Moving Object Segmentation
Multi-Frame Recurrent Adversarial Network for Moving Object Segmentation
Showing a sample of 109 resources. View the full list on GitHub →