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awesome-background-subtraction
A curated list of background subtraction related papers and resources
https://github.com/murari023/awesome-background-subtraction
Last synced: 5 days ago
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2018 Papers
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Conference
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Multi-scale Recurrent Encoder-Decoder Network for Dense Temporal Classification - 2018**)
- 2018 - MsEDNet: Multi-Scale Deep Saliency Learning for Moving Object Detection - 2018**)
- 2018 - Foreground Detection in Surveillance Video with Fully Convolutional Semantic Network - 2018**)
- 2018 - Local Compact Binary Patterns for Background Subtraction in Complex Scenes - 2018**)
- 2018 - A Co-occurrence Background Model with Hypothesis on Degradation Modification for Object Detection in Strong Background Changes - 2018**)
- 2018 - Background Subtraction via 3D Convolutional Neural Networks - 2018**)
- 2018 - ReMotENet Efficient Relevant Motion Event Detection for Large-scale Home Surveillance Videos - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2019 - FgGAN A Cascaded Unpaired Learning for Background Estimation and Foreground Segmentation
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2019 - Illumination-Aware Multi-Task GANs for Foreground Segmentation
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - BSCGAN: Deep Background Subtraction with Conditional Generative Adversarial Networks
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
- 2018 - Learning Background Subtraction by Video Synthesis and Multi-scale Recurrent Networks - 2018**)
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Journals
- 2018 - MSFgNet: A Novel Compact End-to-End Deep Network for Moving Object Detection - IEEE Transactions on Intelligent Transportation Systems**)
- 2018 - A Foreground Inference Network for Video Surveillance Using Multi-View Receptive Field - 2018**)
- 2018 - Change Detection by Training a Triplet Network for Motion Feature Extraction - IEEE Transactions on Circuits and Systems for Video Technology**)
- 2018 - Multiscale Fully Convolutional Network for Foreground Object Detection in Infrared Videos - IEEE Geoscience and Remote Sensing Letters**)
- 2018 - Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding - anggun/FgSegNet) (**2018-Arxiv**)
- 2018 - Deep Background Modeling Using Fully Convolutional Network - IEEE Transactions on Intelligent Transportation Systems**)
- 2018 - Foreground segmentation using convolutional neural networks for multiscale feature encoding - Pattern Recognition Letters, Elsevier**)
- 2018 - A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction - IEEE Access**)
- 2018 - A novel framework for background subtraction and foreground detection - Pattern Recognition, Elsevier**)
- 2018 - Learning Multi-scale Features for Foreground Segmentation - Arxiv**)
- 2018 - MPNET: An End-to-End Deep Neural Network for Object Detection in Surveillance Video - IEEE Access**)
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2021 Papers
- 2021 - BSUV-Net 2.0: Spatio-Temporal Data Augmentations for Video-Agnostic Supervised Background Subtraction
- 2021 - Multi-Frame Recurrent Adversarial Network for Moving Object Segmentation - 2021**)
- 2021 - Deep Adversarial Network for Scene Independent Moving Object Segmentation
- 2021 - End-to-End Recurrent Generative Adversarial Network for Traffic and Surveillance Applications
- 2021 - An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs
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2020 Papers
- 2020 - Graph Moving Object Segmentation - IEEE Transactions on Pattern Analysis and Machine Intelligence**) [**Source Code**](https://github.com/jhonygiraldo/GraphMOS)
- 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 - 2020**)
- 2020 - MotionRec: Unified Deep Framework for Moving Object Recognition - kush/MotionRec)
- 2020 - BSUV-Net: A Fully-Convolutional Neural Network for Background Subtraction of Unseen Videos - Net-inference)
- 2020 - Semi-supervised Background Subtraction of Unseen Videos: Minimization of the Total Variation of Graph Signals
- 2020 - MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos - MM 2020**)
- 2020 - Scene Independency Matters: An Empirical Study of Scene Dependent and Scene Independent Evaluation for CNN-Based Change Detection - IEEE Transactions on Intelligent Transportation Systems**)
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2019 Papers
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Journals
- 2019 - 3DFR: A Swift 3D Feature Reductionist Framework for Scene Independent Change Detection - IEEE Signal Processing Letters**)
- 2019 - vsEnDec: An improved image to image CNN for foreground localization - IEEE Transactions on Intelligent Transportation Systems**)
- 2019 - Deep neural network concepts for background subtraction: A systematic review and comparative evaluation - Neural Networks, Elsevier**)
- 2019 - Panoramic Background Image Generation for PTZ Cameras - IEEE Transactions on Image Processing**)
- 2019 - Moving Object Detection Through Image Bit-Planes Representation Without Thresholding - IEEE Transactions on Intelligent Transportation Systems**)
- 2019 - Rapid and Robust Background Modeling Technique for Low-Cost Road Traffic Surveillance Systems - IEEE Transactions on Intelligent Transportation Systems**)
- 2019 - Foreground Segmentation Using Adaptive 3 Phase Background Model - IEEE Transactions on Intelligent Transportation Systems**)
- 2019 - A 3D CNN-LSTM-Based Image-to-Image Foreground Segmentation - IEEE Transactions on Intelligent Transportation Systems**)
- 2019 - Salient Features for Moving Object Detection in Adverse Weather Conditions during Night Time - IEEE Transactions on Circuits and Systems for Video Technology**)
- 2019 - Moving object detection in complex scene using spatiotemporal structured-sparse RPCA - IEEE Transactions on Image Processing**)
- 2019 - Refining background subtraction using consistent motion detection in adverse weather - Journal of Electronic Imaging**)
- 2019 - DeepPBM: Deep Probabilistic Background Model Estimation from Video Sequences - Arxiv**)
- 2019 - Combining Background Subtraction Algorithms with Convolutional Neural Network - Journal of Electronic Imaging**)
- 2019 - DeepPBM: Deep Probabilistic Background Model Estimation from Video Sequences - Arxiv**)
- 2019 - Video Foreground Extraction Using Multi-View Receptive Field and Encoder–Decoder DCNN for Traffic and Surveillance Applications - IEEE Transactions on Vehicular Technology**)
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Conferences
- 2019 - Simple background subtraction constraint for weakly supervised background subtraction network
- 2019 - Unsupervised moving object detection via contextual information separation
- 2019 - Learning to See Moving Objects in the Dark - 2019**)
- 2019 - Motion Saliency Based Generative Adversarial Network for Underwater Moving Object Segmentation
- 2019 - Panoramic Video Separation with Online Grassmannian Robust Subspace Estimation
- 2019 - Rapid Technique to Eliminate Moving Shadows for Accurate Vehicle Detection
- 2019 - Online and batch supervised background estimation via L1 regression
- 2019 - TU-VDN: Tripura University Video Dataset at Night Time in Degraded Atmospheric Outdoor Conditions for Moving Object Detection
- 2019 - Detection of Dynamic Objects in Videos Using LBSP and Fuzzy Gray Level Difference Histograms - 2019**)
- 2019 - Moving Object Detection Under Discontinuous Change in Illumination Using Tensor Low-Rank and Invariant Sparse Decomposition - 2019**)
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2017 Papers
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Conference
- 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
- 2017 - Interactive deep learning method for segmenting moving objects
- 2017 - End-to-end video background subtraction with 3D convolutional neural networks
- 2017 - Foreground Segmentation for Anomaly Detection in Surveillance Videos Using Deep Residual Networks - segmentation)
- 2017 - Learning deep structured network for weakly supervised change detection
- 2017 - Analytics of deep neural network in change detection
- 2017 - Background modelling based on generative unet
- 2017 - Joint Background Reconstruction and Foreground Segmentation via a Two-Stage Convolutional Neural Network
- 2017 - Pixel-wise Deep Sequence Learning for Moving Object Detection
- 2017 - WiSARDrp for Change Detection in Video Sequences - 2017**)
- 2017 - A Deep Convolutional Neural Network for Background Subtraction
- 2017 - A Deep Convolutional Neural Network for Background Subtraction
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2016 Papers
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Non-Deep Learning based Papers
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Landmark Papers in Background Subtraction
- 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
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2018 Papers
- 2018 - M4CD A Robust Change Detection Method for Intelligent Visual Surveillance
- 2018 - ANTIC: ANTithetic Isomeric Cluster Patterns for Medical Image Retrieval and Change Detection
- 2018 - Multi-scale Recurrent Encoder-Decoder Network for Dense Temporal Classification
- 2018 - A New Foreground Segmentation Method for Video Analysis in Different Color Spaces
- 2018 - Background subtraction via 3D convolutional neural networks
- 2018 - Local Compact Binary Patterns for Background Subtraction in Complex Scenes
- 2018 - Unsupervised deep context prediction for background estimation and foreground segmentation
- 2018 - CANDID:Robust Change Dynamics and Deterministic Update Policy for Dynamic Background Subtraction
- 2018 - Unsupervised deep context prediction for background estimation and foreground segmentation
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Review/survey Papers
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2017 Papers
- 2019 - Background Subtraction in Real Applications: Challenges, Current Models and Future Directions
- 2018 - New trend in video foreground detection using deep learning
- 2014 - Traditional and recent approaches in background modeling for foreground detection: An overview
- 2019 - Background Subtraction in Real Applications: Challenges, Current Models and Future Directions
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Datasets
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Awesome Researchers
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2017 Papers
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Awesome Resources
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