A curated list of background subtraction papers and related applications resources
- Deep Learning based Papers
- GAN Based Papers
- Non-Deep Learning based Papers
- Review/survey papers
- Datasets
- Awesome Researchers
- Awesome Resources
- Projects
2018 Papers, 2017 Papers, 2016 Papers
- 2018 - Foreground Detection in Surveillance Video with Fully Convolutional Semantic Network
- 2018 - BSCGAN: Deep Background Subtraction with Conditional Generative Adversarial Networks
- 2018 - Combining Background Subtraction Algorithms with Convolutional Neural Network
- 2018 - A Foreground Inference Network for Video Surveillance Using Multi-View Receptive Field
- 2018 - Change Detection by Training a Triplet Network for Motion Feature Extraction
- 2018 - Multiscale Fully Convolutional Network for Foreground Object Detection in Infrared Videos
- 2018 - ReMotENet Efficient Relevant Motion Event Detection for Large-scale Home Surveillance Videos
- 2018 - WiSARDrp for Change Detection in Video Sequences
- 2018 - Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding, Source Code
- 2018 - Deep Background Modeling Using Fully Convolutional Network
- 2018 - A deep convolutional neural network for video sequence background subtraction
- 2018 - Foreground segmentation using convolutional neural networks for multiscale feature encoding
- 2018 - A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction
- 2018 - A novel framework for background subtraction and foreground detection
- 2018 - Learning Multi-scale Features for Foreground Segmentation
- 2018 - MPNET: An End-to-End Deep Neural Network for Object Detection in Surveillance Video
- 2017 - Foreground Segmentation for Anomaly Detection in Surveillance Videos Using Deep Residual Networks, Source Code
- 2017 - Learning deep structured network for weakly supervised change detection
- 2017 - A Deep Convolutional Neural Network for Background Subtraction
- 2017 - Analytics of deep neural network in change detection
- 2017 - Background modelling based on generative unet
- 2017 - Background subtraction using encoder-decoder structured convolutional neural network
- 2017 - FusionSeg Learning to combine motion and appearance for fully automatic segmention of generic objects in videos, Source Code
- 2017 - Interactive deep learning method for segmenting moving objects, Source Code
- 2017 - Joint Background Reconstruction and Foreground Segmentation via a Two-Stage Convolutional Neural Network
- 2017 - Pixel-wise Deep Sequence Learning for Moving Object Detection
Landmark Papers, 2018 Papers, 2017 Papers, 2016 Papers, 2015 Papers
- 2015 - SuBSENSE - A Universal Change Detection Method With Local Adaptive Sensitivity
- 2012 - PBAS - Background Segmentation with Feedback: The Pixel-Based Adaptive Segmenter
- 2011 - ViBe: A Universal Background Subtraction Algorithm for Video Sequences
- 2006 - A Texture-Based Method for Modeling the Background and Detecting Moving Objects
- 1999 - Adaptive background mixture models for real-time tracking
- 2018 - A Background Modeling and Foreground Detection Algorithm Using Scaling Coefficients Defined With a Color Model Called Lightness-Red-Green-Blue
- 2018 - M4CD A Robust Change Detection Method for Intelligent Visual Surveillance
- 2018 - CANDID:Robust Change Dynamics and Deterministic Update Policy for Dynamic Background Subtraction
- 2018 - ANTIC: ANTithetic Isomeric Cluster Patterns for Medical Image Retrieval and Change Detection
- Change Detection Net (CDNet)
- Scene Back Modelling (SBMNet)
- SBI
- SBM-RGBD
- Wallflower
- fish4knowledge
- MARDCT
- MuHavi
- LASIESTA
- [Background subtraction using deep learning method by Yiqi Yan](https://github.com/SaoYan/bgsCNN)
If you have any suggestions (missing papers, projects, source code, new papers, key researchers, dataset, etc.), please feel free to edit and pull a request. (or just let me know the title of paper)