On the public citation graph

Detection of Moving Object Using Superpixel Fusion Network

0 signed · 71 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

1 of the 53 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1007/s11042-018-6710-1 (notice 2022-09-13).

Dataset join, best-effort; this page does not check the publisher record. Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0); dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01234-2_22openalex-snapshot

Superpixel Sampling Networks

inferredcites →https://doi.org/10.1007/978-3-319-46448-0_36openalex-snapshot

Superpixel Convolutional Networks Using Bilateral Inceptions

inferredcites →https://doi.org/10.1007/978-981-10-3002-4_33openalex-snapshot

Background Subtraction Based on Superpixels Under Multi-scale in Complex Scenes

inferredcites →https://doi.org/10.1007/s00371-021-02286-0openalex-snapshot

Background subtraction for moving object detection: explorations of recent developments and challenges

inferredcites →https://doi.org/10.1007/s11042-018-6710-1openalex-snapshot

RETRACTED ARTICLE: Moving object detection based on smoothing three frame difference method fused with RPCA

inferredcites →https://doi.org/10.1007/s11042-021-11548-xopenalex-snapshot

An improved statistical approach for moving object detection in thermal video frames

inferredcites →https://doi.org/10.1007/s11042-022-12832-0openalex-snapshot

Moving object detection for unseen videos via truncated weighted robust principal component analysis and salience convolution neural network

inferredcites →https://doi.org/10.1007/s11263-015-0822-0openalex-snapshot

SuperCNN: A Superpixelwise Convolutional Neural Network for Salient Object Detection

inferredcites →https://doi.org/10.1007/s11554-020-01058-8openalex-snapshot

Fast background subtraction with adaptive block learning using expectation value suitable for real-time moving object detection

inferredcites →https://doi.org/10.1007/s41095-018-0123-yopenalex-snapshot

FLIC: Fast linear iterative clustering with active search

inferredcites →https://doi.org/10.1016/j.eswa.2021.116306openalex-snapshot

Enhanced the moving object detection and object tracking for traffic surveillance using RBF-FDLNN and CBF algorithm

inferredcites →https://doi.org/10.1016/j.infrared.2018.05.009openalex-snapshot

Combination of local binary pattern operator with sample consensus model for moving objects detection

inferredcites →https://doi.org/10.1016/j.neucom.2018.10.012openalex-snapshot

Moving object detection via segmentation and saliency constrained RPCA

inferredcites →https://doi.org/10.1016/j.neucom.2019.12.104openalex-snapshot

Change detection based on tensor RPCA for longitudinal retinal fundus images

inferredcites →https://doi.org/10.1016/j.patrec.2018.08.002openalex-snapshot

Foreground segmentation using convolutional neural networks for multiscale feature encoding

inferredcites →https://doi.org/10.1016/j.patrec.2019.11.004openalex-snapshot

Moving object detection under different weather conditions using full-spectrum light sources

inferredcites →https://doi.org/10.1109/access.2018.2846678openalex-snapshot

Background Subtraction Based on Random Superpixels Under Multiple Scales for Video Analytics

inferredcites →https://doi.org/10.1109/access.2021.3123975openalex-snapshot

A Fast Lightweight 3D Separable Convolutional Neural Network With Multi-Input Multi-Output for Moving Object Detection

inferredcites →https://doi.org/10.1109/cvpr.1999.784637openalex-snapshot

Adaptive background mixture models for real-time tracking

inferredcites →https://doi.org/10.1109/cvpr.2015.7299114openalex-snapshot

Superpixel-based video object segmentation using perceptual organization and location prior

inferredcites →https://doi.org/10.1109/cvpr.2019.00097openalex-snapshot

Unsupervised Moving Object Detection via Contextual Information Separation

inferredcites →https://doi.org/10.1109/cvprw.2012.6238925openalex-snapshot

Background segmentation with feedback: The Pixel-Based Adaptive Segmenter

inferredcites →https://doi.org/10.1109/cvprw.2014.126openalex-snapshot

CDnet 2014: An Expanded Change Detection Benchmark Dataset

inferredcites →https://doi.org/10.1109/iccvw.2015.123openalex-snapshot

Background Subtraction via Superpixel-Based Online Matrix Decomposition with Structured Foreground Constraints

inferredcites →https://doi.org/10.1109/iccvw54120.2021.00030openalex-snapshot

Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos

inferredcites →https://doi.org/10.1109/icip.2018.8451603openalex-snapshot

BSCGAN: Deep Background Subtraction with Conditional Generative Adversarial Networks

inferredcites →https://doi.org/10.1109/icip40778.2020.9190734openalex-snapshot

CS-RPCA: Clustered Sparse RPCA for Moving Object Detection

inferredcites →https://doi.org/10.1109/icip40778.2020.9191151openalex-snapshot

Rethinking Background And Foreground In Deep Neural Network-Based Background Subtraction

inferredcites →https://doi.org/10.1109/icsp14105.2008openalex-snapshot

2008 9th International Conference on Signal Processing

inferredcites →https://doi.org/10.1109/iscas45731.2020.9181053openalex-snapshot

A Super-Fast Deep Network for Moving Object Detection

inferredcites →https://doi.org/10.1109/jstars.2021.3052968openalex-snapshot

Visual Attention and Background Subtraction With Adaptive Weight for Hyperspectral Anomaly Detection

inferredcites →https://doi.org/10.1109/smc.2018.00289openalex-snapshot

MsEDNet: Multi-Scale Deep Saliency Learning for Moving Object Detection

inferredcites →https://doi.org/10.1109/ssp.2018.8450718openalex-snapshot

Robust PCA and Robust Subspace Tracking: A Comparative Evaluation

inferredcites →https://doi.org/10.1109/tii.2018.2873492openalex-snapshot

Deep Learning and Superpixel Feature Extraction Based on Contractive Autoencoder for Change Detection in SAR Images

inferredcites →https://doi.org/10.1109/tip.2010.2101613openalex-snapshot

ViBe: A Universal Background Subtraction Algorithm for Video Sequences

inferredcites →https://doi.org/10.1109/tip.2018.2874289openalex-snapshot

Moving Object Detection in Complex Scene Using Spatiotemporal Structured-Sparse RPCA

inferredcites →https://doi.org/10.1109/tip.2020.3037472openalex-snapshot

3DCD: Scene Independent End-to-End Spatiotemporal Feature Learning Framework for Change Detection in Unseen Videos

inferredcites →https://doi.org/10.1109/tip.2021.3122102openalex-snapshot

Meta-Knowledge Learning and Domain Adaptation for Unseen Background Subtraction

inferredcites →https://doi.org/10.1109/tits.2018.2880096openalex-snapshot

MSFgNet: A Novel Compact End-to-End Deep Network for Moving Object Detection

inferredcites →https://doi.org/10.1109/tits.2021.3077883openalex-snapshot

An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs

inferredcites →https://doi.org/10.1109/tmm.2020.3006419openalex-snapshot

Unsupervised Moving Object Detection in Complex Scenes Using Adversarial Regularizations

inferredcites →https://doi.org/10.1109/tpami.2017.2717828openalex-snapshot

Spatiotemporal GMM for Background Subtraction with Superpixel Hierarchy

inferredcites →https://doi.org/10.1109/tpami.2020.3042093openalex-snapshot

Graph Moving Object Segmentation

inferredcites →https://doi.org/10.1109/wacv45572.2020.9093464openalex-snapshot

BSUV-Net: A Fully-Convolutional Neural Network for Background Subtraction of Unseen Videos

inferredcites →https://doi.org/10.1117/1.jei.27.2.023002openalex-snapshot

SWCD: a sliding window and self-regulated learning-based background updating method for change detection in videos

inferredcites →https://doi.org/10.1145/1236471.1236475openalex-snapshot

Segmentation and recognition of motion streams by similarity search

inferredcites →https://doi.org/10.1145/1970392.1970395openalex-snapshot

Robust principal component analysis?

inferredcites →https://doi.org/10.1145/3106156openalex-snapshot

Sparse Representation-Based Semi-Supervised Regression for People Counting

inferredcites →https://doi.org/10.1145/3131342openalex-snapshot

An Efficient Motion Detection and Tracking Scheme for Encrypted Surveillance Videos

inferredcites →https://doi.org/10.1145/3407188openalex-snapshot

Motion-Aware Structured Matrix Factorization for Foreground Detection in Complex Scenes

inferredcites →https://doi.org/10.1145/3440694openalex-snapshot

Residual Refinement Network with Attribute Guidance for Precise Saliency Detection

inferredcites →https://doi.org/10.2174/1874479611104030147openalex-snapshot

Recent Advanced Statistical Background Modeling for Foreground Detection - A Systematic Survey

inferredcites →https://doi.org/10.3390/jimaging4060078openalex-snapshot

Analytics of Deep Neural Network-Based Background Subtraction

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-77789-9_7openalex-snapshot

Efficient Generation of Synthetic Breast CT Slices By Combining Generative and Super-Resolution Models

inferred← citeshttps://doi.org/10.1007/978-981-96-5969-2_27openalex-snapshot

Object Detection in Videos: Hitherto and Future Perspectives

inferred← citeshttps://doi.org/10.1007/s00521-025-11122-8openalex-snapshot

Zero-shot image segmentation for scene objects based on the L0 gradient minimization and adaptive superpixel method

inferred← citeshttps://doi.org/10.1007/s11042-023-16595-0openalex-snapshot

Handling illumination variation for motion detection in video through intelligent method: An application for smart surveillance system

inferred← citeshttps://doi.org/10.1007/s11227-025-08105-wopenalex-snapshot

Frequency domain discrimination and double loss function optimization of image generation for GANs

inferred← citeshttps://doi.org/10.1007/s11263-024-02268-4openalex-snapshot

One-Shot Generative Domain Adaptation in 3D GANs

inferred← citeshttps://doi.org/10.1016/j.cag.2023.08.016openalex-snapshot

W2 GAN: Importance Weight and Wavelet feature guided Image-to-Image translation under limited data

inferred← citeshttps://doi.org/10.1016/j.compmedimag.2024.102332openalex-snapshot

Multi-modal brain tumor segmentation via conditional synthesis with Fourier domain adaptation

inferred← citeshttps://doi.org/10.1016/j.imavis.2026.106114openalex-snapshot

Ghost-free multi-exposure image fusion based on dual weights

inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128965openalex-snapshot

Content-aware preserving image generation

inferred← citeshttps://doi.org/10.1016/j.optlastec.2024.112028openalex-snapshot

Sparse holographic tomography reconstruction method based on self-supervised neural network with learning to synthesize strategy

inferred← citeshttps://doi.org/10.1016/j.optlastec.2025.113693openalex-snapshot

Dual attention-assisted HDR light field imaging using state space model and implicit neural representation

inferred← citeshttps://doi.org/10.1109/tip.2024.3378473openalex-snapshot

Learning Temporal Distribution and Spatial Correlation Toward Universal Moving Object Segmentation

inferred← citeshttps://doi.org/10.1117/12.3045893openalex-snapshot

AdverX-Ray: ensuring x-ray integrity through frequency-sensitive adversarial VAEs

inferred← citeshttps://doi.org/10.1145/3662185openalex-snapshot

EOGT: Video Anomaly Detection with Enhanced Object Information and Global Temporal Dependency

inferred← citeshttps://doi.org/10.1145/3702640openalex-snapshot

Toward Oriented Fisheye Object Detection: Dataset and Baseline

inferred← citeshttps://doi.org/10.3390/electronics12051259openalex-snapshot

Detecting Human Falls in Poor Lighting: Object Detection and Tracking Approach for Indoor Safety

inferred← citeshttps://doi.org/10.3390/rs15102541openalex-snapshot

DILRS: Domain-Incremental Learning for Semantic Segmentation in Multi-Source Remote Sensing Data

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.