On the public citation graph
Understanding the Challenges and Opportunities of Pose-based Anomaly Detection
0 signed · 38 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.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
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known work and none has been retracted — and get a dated CiteStamped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.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-031-19778-9_42openalex-snapshot
Self-supervised Sparse Representation for Video Anomaly Detection
inferredcites →https://doi.org/10.1007/s13735-022-00227-8openalex-snapshot
Anomaly detection using edge computing in video surveillance system: review
inferredcites →https://doi.org/10.1016/j.aei.2021.101471openalex-snapshot
Deep-learning-based anomaly detection for lace defect inspection employing videos in production line
inferredcites →https://doi.org/10.1016/j.neucom.2019.12.148openalex-snapshot
Normal graph: Spatial temporal graph convolutional networks based prediction network for skeleton based video anomaly detection
inferredcites →https://doi.org/10.1016/j.neucom.2021.12.023openalex-snapshot
Human-related anomalous event detection via spatial-temporal graph convolutional autoencoder with embedded long short-term memory network
inferredcites →https://doi.org/10.1016/j.optlaseng.2020.106324openalex-snapshot
Semi-supervised anomaly detection with dual prototypes autoencoder for industrial surface inspection
inferredcites →https://doi.org/10.1016/j.patcog.2021.108232openalex-snapshot
Spatiotemporal consistency-enhanced network for video anomaly detection
inferredcites →https://doi.org/10.1109/avss.2019.8909844openalex-snapshot
Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00678openalex-snapshot
Real-World Anomaly Detection in Surveillance Videos
inferredcites →https://doi.org/10.1109/cvpr.2019.01227openalex-snapshot
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01055openalex-snapshot
Graph Embedded Pose Clustering for Anomaly Detection
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01433openalex-snapshot
Generative Cooperative Learning for Unsupervised Video Anomaly Detection
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01951openalex-snapshot
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection
inferredcites →https://doi.org/10.1109/iccv.2017.45openalex-snapshot
A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework
inferredcites →https://doi.org/10.1109/iccv48922.2021.00493openalex-snapshot
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning
inferredcites →https://doi.org/10.1109/iccv51070.2023.01246openalex-snapshot
Normalizing Flows for Human Pose Anomaly Detection
inferredcites →https://doi.org/10.1109/mits.2021.3049404openalex-snapshot
Vehicle Trajectory Prediction Using LSTMs With Spatial–Temporal Attention Mechanisms
inferredcites →https://doi.org/10.1109/tits.2022.3172015openalex-snapshot
DeepTrack: Lightweight Deep Learning for Vehicle Trajectory Prediction in Highways
inferredcites →https://doi.org/10.1109/tpami.2013.111openalex-snapshot
Anomaly Detection and Localization in Crowded Scenes
inferredcites →https://doi.org/10.1109/tpami.2019.2944377openalex-snapshot
Video Anomaly Detection with Sparse Coding Inspired Deep Neural Networks
inferredcites →https://doi.org/10.1109/tpami.2022.3222784openalex-snapshot
AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time
inferredcites →https://doi.org/10.1109/wacv45572.2020.9093633openalex-snapshot
Multi-timescale Trajectory Prediction for Abnormal Human Activity Detection
inferredcites →https://doi.org/10.1109/wacv51458.2022.00309openalex-snapshot
Rethinking Video Anomaly Detection - A Continual Learning Approach
inferredcites →https://doi.org/10.1145/3385809openalex-snapshot
Coupled IGMM-GANs with Applications to Anomaly Detection in Human Mobility Data
inferredcites →https://doi.org/10.1371/journal.pone.0118432openalex-snapshot
The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets
inferredcites →https://doi.org/10.3390/app12010004openalex-snapshot
A Self-Attention Augmented Graph Convolutional Clustering Networks for Skeleton-Based Video Anomaly Behavior Detection
inferredcites →https://doi.org/10.3390/electronics11193105openalex-snapshot
Crowd Anomaly Detection in Video Frames Using Fine-Tuned AlexNet Model
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4672585openalex-extracted
Exploring Public's Perception of Safety and Video Surveillance
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.123135openalex-snapshot
Detecting video anomalies by jointly utilizing appearance and skeleton information
inferred← citeshttps://doi.org/10.1016/j.iot.2025.101716openalex-snapshot
From lab to field: Real-world evaluation of an AI-driven Smart Video Solution to enhance community safety
inferred← citeshttps://doi.org/10.1016/j.techfore.2026.124879openalex-snapshot
Co-creating responsible AI for public safety: A mixed-method approach toward understanding stakeholder perceptions
inferred← citeshttps://doi.org/10.1016/j.techsoc.2024.102641openalex-snapshot
Exploring Public's perception of safety and video surveillance technology: A survey approach
inferred← citeshttps://doi.org/10.1109/cvprw63382.2024.00486openalex-snapshot
Evaluating the Effectiveness of Video Anomaly Detection in the Wild Online Learning and Inference for Real-world Deployment
inferred← citeshttps://doi.org/10.1109/iccre61448.2024.10589753openalex-snapshot
Anomaly Detection from Image Classification
inferred← citeshttps://doi.org/10.1109/tcsvt.2025.3632768openalex-snapshot
Toward Adaptive Human-Centric Video Anomaly Detection: A Comprehensive Framework and a New Benchmark
inferred← citeshttps://doi.org/10.1109/wacvw60836.2024.00109openalex-snapshot
An Exploratory Study on Human-Centric Video Anomaly Detection through Variational Autoencoders and Trajectory Prediction
inferred← citeshttps://doi.org/10.3390/jimaging12040157openalex-snapshot
A Method for Human Pose Estimation and Joint Angle Computation Through Deep Learning
inferred← citeshttps://doi.org/10.62154/ajastr.2025.021.01012openalex-snapshot
Recent Implementation of Deep Learning Methods for Shoplifting Detection in Retail Environments Using Surveillance Videos
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.