On the public citation graph

Improved Graph Convolutional Network with Enriched Graph Topology Representation for Skeleton-Based Action Recognition

https://doi.org/10.3390/electronics12040879

0 signed · 84 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.

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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/978-3-030-58555-6_20openalex-snapshot

Clustering Driven Deep Autoencoder for Video Anomaly Detection

inferredcites →https://doi.org/10.1007/978-3-030-58586-0_32openalex-snapshot

Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1007/978-3-030-58610-2_12openalex-snapshot

Single Image Super-Resolution via a Holistic Attention Network

inferredcites →https://doi.org/10.1007/978-3-319-16814-2_4openalex-snapshot

Discriminative Orderlet Mining for Real-Time Recognition of Human-Object Interaction

inferredcites →https://doi.org/10.1007/978-3-319-46487-9_50openalex-snapshot

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

inferredcites →https://doi.org/10.1007/s00521-021-05960-5openalex-snapshot

Advanced metaheuristic optimization techniques in applications of deep neural networks: a review

inferredcites →https://doi.org/10.1016/j.neunet.2021.10.021openalex-snapshot

Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction

inferredcites →https://doi.org/10.1016/j.patcog.2017.02.030openalex-snapshot

Enhanced skeleton visualization for view invariant human action recognition

inferredcites →https://doi.org/10.1016/j.patcog.2018.01.020openalex-snapshot

Multi-stream CNN: Learning representations based on human-related regions for action recognition

inferredcites →https://doi.org/10.1109/access.2020.2972338openalex-snapshot

A Cascaded R-CNN With Multiscale Attention and Imbalanced Samples for Traffic Sign Detection

inferredcites →https://doi.org/10.1109/access.2020.3014445openalex-snapshot

Skeleton-Based Action Recognition Using Multi-Scale and Multi-Stream Improved Graph Convolutional Network

inferredcites →https://doi.org/10.1109/acpr.2015.7486569openalex-snapshot

Skeleton based action recognition with convolutional neural network

inferredcites →https://doi.org/10.1109/cvpr.2014.339openalex-snapshot

Cross-View Action Modeling, Learning, and Recognition

inferredcites →https://doi.org/10.1109/cvpr.2014.82openalex-snapshot

Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group

inferredcites →https://doi.org/10.1109/cvpr.2015.7298714openalex-snapshot

Hierarchical recurrent neural network for skeleton based action recognition

inferredcites →https://doi.org/10.1109/cvpr.2016.115openalex-snapshot

NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.486openalex-snapshot

A New Representation of Skeleton Sequences for 3D Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.51openalex-snapshot

Transition Forests: Learning Discriminative Temporal Transitions for Action Recognition and Detection

inferredcites →https://doi.org/10.1109/cvpr.2018.00558openalex-snapshot

Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2018.00745openalex-snapshot

Squeeze-and-Excitation Networks

inferredcites →https://doi.org/10.1109/cvpr.2019.00060openalex-snapshot

Selective Kernel Networks

inferredcites →https://doi.org/10.1109/cvpr.2019.00132openalex-snapshot

An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2019.00371openalex-snapshot

Actional-Structural Graph Convolutional Networks for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2019.01230openalex-snapshot

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00022openalex-snapshot

Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00026openalex-snapshot

Skeleton-Based Action Recognition With Shift Graph Convolutional Network

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00119openalex-snapshot

Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00325openalex-snapshot

Relation-Aware Global Attention for Person Re-Identification

inferredcites →https://doi.org/10.1109/cvpr42600.2020.01009openalex-snapshot

Exploring Self-Attention for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr52688.2022.01955openalex-snapshot

InfoGCN: Representation Learning for Human Skeleton-based Action Recognition

inferredcites →https://doi.org/10.1109/cvprw.2012.6239233openalex-snapshot

View invariant human action recognition using histograms of 3D joints

inferredcites →https://doi.org/10.1109/iccv.2015.460openalex-snapshot

Differential Recurrent Neural Networks for Action Recognition

inferredcites →https://doi.org/10.1109/iccv.2017.115openalex-snapshot

Ensemble Deep Learning for Skeleton-Based Action Recognition Using Temporal Sliding LSTM Networks

inferredcites →https://doi.org/10.1109/iccv.2017.233openalex-snapshot

View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data

inferredcites →https://doi.org/10.1109/iccv48922.2021.01311openalex-snapshot

Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/icmew.2017.8026282openalex-snapshot

Skeleton based action recognition using translation-scale invariant image mapping and multi-scale deep CNN

inferredcites →https://doi.org/10.1109/tcsvt.2018.2864148openalex-snapshot

Action Recognition With Spatio–Temporal Visual Attention on Skeleton Image Sequences

inferredcites →https://doi.org/10.1109/tcsvt.2020.3015051openalex-snapshot

Richly Activated Graph Convolutional Network for Robust Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/tip.2019.2937724openalex-snapshot

EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks

inferredcites →https://doi.org/10.1109/tip.2020.3028207openalex-snapshot

Skeleton-Based Action Recognition With Multi-Stream Adaptive Graph Convolutional Networks

inferredcites →https://doi.org/10.1109/tmm.2022.3151145openalex-snapshot

Learning Cross-Channel Representations for Semantic Segmentation

inferredcites →https://doi.org/10.1109/tmm.2022.3168137openalex-snapshot

Joint-Bone Fusion Graph Convolutional Network for Semi-Supervised Skeleton Action Recognition

inferredcites →https://doi.org/10.1109/tnnls.2021.3061115openalex-snapshot

Memory Attention Networks for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/tpami.2013.198openalex-snapshot

Learning Actionlet Ensemble for 3D Human Action Recognition

inferredcites →https://doi.org/10.1109/tpami.2022.3152247openalex-snapshot

A Survey on Vision Transformer

inferredcites →https://doi.org/10.1109/wacv56688.2023.00333openalex-snapshot

STAR-Transformer: A Spatio-temporal Cross Attention Transformer for Human Action Recognition

inferredcites →https://doi.org/10.1145/3394171.3413802openalex-snapshot

Stronger, Faster and More Explainable: A Graph Convolutional Baseline for Skeleton-based Action Recognition

inferredcites →https://doi.org/10.1145/3394171.3413941openalex-snapshot

Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition

inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot

Long Short-Term Memory

inferredcites →https://doi.org/10.1609/aaai.v31i1.11212openalex-snapshot

An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data

inferredcites →https://doi.org/10.1609/aaai.v32i1.12328openalex-snapshot

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1609/aaai.v33i01.33018561openalex-snapshot

Spatio-Temporal Graph Routing for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.3115/v1/d14-1179openalex-snapshot

Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

inferredcites →https://doi.org/10.3390/s19010059openalex-snapshot

Hand Gesture Recognition in Automotive Human–Machine Interaction Using Depth Cameras

inferredcites →https://doi.org/10.48550/arxiv.1407.3068openalex-snapshot

Deep Networks with Internal Selective Attention through Feedback Connections

inferredcites →https://doi.org/10.48550/arxiv.1606.09375openalex-snapshot

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-981-95-8232-7_26openalex-snapshot

Patient Behavior Recognition Methods Based on WIFI-CSI Features

inferred← citeshttps://doi.org/10.1007/s10489-024-06131-4openalex-snapshot

Entity alignment in noisy knowledge graph

inferred← citeshttps://doi.org/10.1007/s10489-025-06283-xopenalex-snapshot

Hypergraph denoising neural network for session-based recommendation

inferred← citeshttps://doi.org/10.1007/s10489-025-06469-3openalex-snapshot

2D-Variation convolution-based generative adversarial network for unsupervised time series anomaly detection: a MSTL enhanced data preprocessing approach

inferred← citeshttps://doi.org/10.1007/s10489-025-06642-8openalex-snapshot

How to learn new knowledge: a multimodal contrastive learning framework for open-world knowledge graph completion

inferred← citeshttps://doi.org/10.1007/s41748-026-01035-4openalex-snapshot

Integrating Google Earth Engine and Machine Learning To Map LULC and LST Dynamics in the Arid Heartland of Pakistan

inferred← citeshttps://doi.org/10.1007/s44443-026-00698-3openalex-snapshot

Availability stress analysis of DDoS traffic with implications for cryptocurrency infrastructure

inferred← citeshttps://doi.org/10.1016/j.aei.2026.104440openalex-snapshot

A dual-dynamic deep learning model with graph Kolmogorov–Arnold networks and Bi-GRU for seismic power spectral prediction

inferred← citeshttps://doi.org/10.1016/j.aej.2025.03.010openalex-snapshot

An improved and decentralized/distributed healthcare framework for disabled people through AI models

inferred← citeshttps://doi.org/10.1016/j.aej.2025.07.044openalex-snapshot

ConFirePatch: Context-based fire detection and segmentation via extracting key patches

inferred← citeshttps://doi.org/10.1016/j.energy.2025.136725openalex-snapshot

A simple yet effective multivariate long sequence wind speed prediction model for urban blocks with spatio-temporal feature embedding

inferred← citeshttps://doi.org/10.1016/j.eswa.2026.132073openalex-snapshot

Subspace information imputation-assisted global-nonlocal high-order structural representation for hyperspectral image completing and mixed denoising

inferred← citeshttps://doi.org/10.1016/j.eswa.2026.133075openalex-snapshot

A bimodal surrogate-assisted PSO algorithm with wide coverage and dynamic space refinement for expensive multi-UAV path planning

inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103262openalex-snapshot

CCF: Cross Correcting Framework for pedestrian trajectory prediction in multi-agent traffic scenarios

inferred← citeshttps://doi.org/10.1016/j.knosys.2024.112319openalex-snapshot

Variation-aware directed graph convolutional networks for skeleton-based action recognition

inferred← citeshttps://doi.org/10.1016/j.neunet.2025.107504openalex-snapshot

Interpretable unsupervised neural network structure for data clustering via differentiable reconstruction of ONMF and sparse autoencoder

inferred← citeshttps://doi.org/10.1016/j.neunet.2026.109369openalex-snapshot

Physics-constrained machine learning for impedance-based measurement and sound absorption prediction of composite acoustic materials

inferred← citeshttps://doi.org/10.1049/itr2.70188openalex-snapshot

A Two‐Stage SlowFast‐YE Network for Robust Recognition of Crew Irregularities on the Bridge

inferred← citeshttps://doi.org/10.1109/access.2024.3359234openalex-snapshot

Multi-Scale Adaptive Graph Convolution Network for Skeleton-Based Action Recognition

inferred← citeshttps://doi.org/10.1109/access.2024.3454170openalex-snapshot

Using Hybrid Models for Action Correction in Instrument Learning Based on AI

inferred← citeshttps://doi.org/10.1109/access.2024.3477321openalex-snapshot

PH-GCN: Boosting Human Action Recognition Through Multi-Level Granularity With Pair-Wise Hyper GCN

inferred← citeshttps://doi.org/10.1109/access.2024.3492332openalex-snapshot

Topology Learning by Context Embedding and Channel Refinement for Skeletal Behavior Recognition

inferred← citeshttps://doi.org/10.1109/fg59268.2024.10582032openalex-snapshot

Human Action Recognition with Multi-Level Granularity and Pair-Wise Hyper GCN

inferred← citeshttps://doi.org/10.1109/tii.2025.3593862openalex-snapshot

Self-Triggered DMPC for Dynamically Coupled Systems With Reduced Conservatism

inferred← citeshttps://doi.org/10.1155/2024/2323337openalex-snapshot

ESTS‐GCN: An Ensemble Spatial–Temporal Skeleton‐Based Graph Convolutional Networks for Violence Detection

inferred← citeshttps://doi.org/10.3390/systems13121113openalex-snapshot

Towards Governance of Socio-Technical System of Systems: Leveraging Lessons from Proven Engineering Principles

inferred← citeshttps://doi.org/10.7717/peerj-cs.3793openalex-snapshot

DTG-LKNet: dual spatio-temporal graphs and large-kernel convolutions network for traffic prediction

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.