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A deep learning method for video‐based action recognition

https://doi.org/10.1049/ipr2.12303
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What this work says

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

inferredcites →https://doi.org/10.1007/11744047_33openalex-snapshot
Human Detection Using Oriented Histograms of Flow and Appearance
inferredcites →https://doi.org/10.1007/978-3-030-01216-8_5openalex-snapshot
CTAP: Complementary Temporal Action Proposal Generation
inferredcites →https://doi.org/10.1007/978-3-030-01225-0_18openalex-snapshot
Spatio-temporal Channel Correlation Networks for Action Classification
inferredcites →https://doi.org/10.1007/978-3-030-01246-5_22openalex-snapshot
Multi-fiber Networks for Video Recognition
inferredcites →https://doi.org/10.1007/978-3-030-01267-0_19openalex-snapshot
Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification
inferredcites →https://doi.org/10.1007/978-3-319-46487-9_47openalex-snapshot
DAPs: Deep Action Proposals for Action Understanding
inferredcites →https://doi.org/10.1007/978-3-540-74936-3_22openalex-snapshot
A Duality Based Approach for Realtime TV-L 1 Optical Flow
inferredcites →https://doi.org/10.1007/978-981-13-2553-3_24openalex-snapshot
Human Activity Recognition in Video Benchmarks: A Survey
inferredcites →https://doi.org/10.1007/s00371-011-0610-yopenalex-snapshot
Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes
inferredcites →https://doi.org/10.1007/s10489-020-01823-zopenalex-snapshot
A combined multiple action recognition and summarization for surveillance video sequences
inferredcites →https://doi.org/10.1007/s11042-018-6935-zopenalex-snapshot
Physics-based keyframe selection for human motion summarization
inferredcites →https://doi.org/10.1016/j.cogsys.2019.03.010openalex-snapshot
Human actions recognition in video scenes from multiple camera viewpoints
inferredcites →https://doi.org/10.1016/j.neucom.2018.11.038openalex-snapshot
Fast and robust dynamic hand gesture recognition via key frames extraction and feature fusion
inferredcites →https://doi.org/10.1109/access.2019.2910604openalex-snapshot
A Spatiotemporal Heterogeneous Two-Stream Network for Action Recognition
inferredcites →https://doi.org/10.1109/cvpr.2005.177openalex-snapshot
Histograms of Oriented Gradients for Human Detection
inferredcites →https://doi.org/10.1109/cvpr.2012.6247807openalex-snapshot
Discovering discriminative action parts from mid-level video representations
inferredcites →https://doi.org/10.1109/cvpr.2014.223openalex-snapshot
Large-Scale Video Classification with Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2015.7298878openalex-snapshot
Long-term recurrent convolutional networks for visual recognition and description
inferredcites →https://doi.org/10.1109/cvpr.2015.7299101openalex-snapshot
Beyond short snippets: Deep networks for video classification
inferredcites →https://doi.org/10.1109/cvpr.2016.119openalex-snapshot
Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs
inferredcites →https://doi.org/10.1109/cvpr.2016.211openalex-snapshot
Fast Temporal Activity Proposals for Efficient Detection of Human Actions in Untrimmed Videos
inferredcites →https://doi.org/10.1109/cvpr.2016.291openalex-snapshot
Actions ~ Transformations
inferredcites →https://doi.org/10.1109/cvpr.2016.297openalex-snapshot
Real-Time Action Recognition with Enhanced Motion Vector CNNs
inferredcites →https://doi.org/10.1109/cvpr.2017.168openalex-snapshot
Deep Temporal Linear Encoding Networks
inferredcites →https://doi.org/10.1109/cvpr.2017.226openalex-snapshot
Spatiotemporal Pyramid Network for Video Action Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.502openalex-snapshot
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
inferredcites →https://doi.org/10.1109/cvpr.2017.675openalex-snapshot
SST: Single-Stream Temporal Action Proposals
inferredcites →https://doi.org/10.1109/cvpr.2018.00054openalex-snapshot
MiCT: Mixed 3D/2D Convolutional Tube for Human Action Recognition
inferredcites →https://doi.org/10.1109/cvpr.2018.00155openalex-snapshot
Appearance-and-Relation Networks for Video Classification
inferredcites →https://doi.org/10.1109/cvpr.2018.00675openalex-snapshot
A Closer Look at Spatiotemporal Convolutions for Action Recognition
inferredcites →https://doi.org/10.1109/cvpr.2019.01232openalex-snapshot
Large-Scale Weakly-Supervised Pre-Training for Video Action Recognition
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00118openalex-snapshot
Gate-Shift Networks for Video Action Recognition
inferredcites →https://doi.org/10.1109/cvprw50498.2020.00346openalex-snapshot
Dynamic Inference: A New Approach Toward Efficient Video Action Recognition
inferredcites →https://doi.org/10.1109/iccv.2011.6126543openalex-snapshot
HMDB: A large video database for human motion recognition
inferredcites →https://doi.org/10.1109/iccv.2013.441openalex-snapshot
Action Recognition with Improved Trajectories
inferredcites →https://doi.org/10.1109/iccv.2015.510openalex-snapshot
Learning Spatiotemporal Features with 3D Convolutional Networks
inferredcites →https://doi.org/10.1109/iccv.2017.317openalex-snapshot
Temporal Action Detection with Structured Segment Networks
inferredcites →https://doi.org/10.1109/iccv.2017.381openalex-snapshot
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-Supervised Object and Action Localization
inferredcites →https://doi.org/10.1109/iccv.2017.392openalex-snapshot
TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals
inferredcites →https://doi.org/10.1109/iccv.2017.590openalex-snapshot
Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks
inferredcites →https://doi.org/10.1109/iccv.2019.00630openalex-snapshot
SlowFast Networks for Video Recognition
inferredcites →https://doi.org/10.1109/jiot.2019.2950469openalex-snapshot
Cost-Effective Video Summarization Using Deep CNN With Hierarchical Weighted Fusion for IoT Surveillance Networks
inferredcites →https://doi.org/10.1109/tcsvt.2019.2890899openalex-snapshot
A Novel Key-Frames Selection Framework for Comprehensive Video Summarization
inferredcites →https://doi.org/10.1109/tip.2018.2890749openalex-snapshot
Action-Stage Emphasized Spatiotemporal VLAD for Video Action Recognition
inferredcites →https://doi.org/10.1109/tpami.2016.2599174openalex-snapshot
Long-Term Recurrent Convolutional Networks for Visual Recognition and Description
inferredcites →https://doi.org/10.1109/tpami.2017.2712608openalex-snapshot
Long-Term Temporal Convolutions for Action Recognition
inferredcites →https://doi.org/10.1109/tpami.2018.2868668openalex-snapshot
Temporal Segment Networks for Action Recognition in Videos
inferredcites →https://doi.org/10.1145/2733373.2806226openalex-snapshot
Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web Images
inferredcites →https://doi.org/10.1609/aaai.v33i01.33018247openalex-snapshot
Attention-Aware Sampling via Deep Reinforcement Learning for Action Recognition
inferredcites →https://doi.org/10.48550/arxiv.1212.0402openalex-snapshot
UCF-101: A dataset of 101 human actions classes from videos in the wild
inferredcites →https://doi.org/10.48550/arxiv.1406.2199openalex-snapshot
Two-Stream Convolutional Networks for Action Recognition in Videos
inferredcites →https://doi.org/10.48550/arxiv.1611.02155openalex-snapshot
Spatiotemporal Residual Networks for Video Action Recognition

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-031-85952-6_38openalex-snapshot
Analysis and Optimization of Track and Field Athletes’ Action Techniques Based on Deep Learning
inferred← citeshttps://doi.org/10.1007/s11227-022-04973-8openalex-snapshot
An attention-based bidirectional GRU network for temporal action proposals generation
inferred← citeshttps://doi.org/10.1016/j.acags.2026.100342openalex-snapshot
Autoregressive model with discrete feature representation for well log interpretation
inferred← citeshttps://doi.org/10.1049/ipr2.12541openalex-snapshot
Video‐based action recognition using spurious‐3D residual attention networks
inferred← citeshttps://doi.org/10.1049/ipr2.12725openalex-snapshot
SRI3D: Two‐stream inflated 3D ConvNet based on sparse regularization for action recognition
inferred← citeshttps://doi.org/10.1109/access.2023.3349020openalex-snapshot
The Computer Vision Simulation of Athlete’s Wrong Actions Recognition Model Based on Artificial Intelligence
inferred← citeshttps://doi.org/10.1109/edpee61724.2024.00191openalex-snapshot
Design of Generative Resource Recommendation Algorithm for Blended Teaching of Government Accounting Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/iist62526.2024.00055openalex-snapshot
Research on the Application of Interactive Intelligent Technology for Action Judgment in Martial Arts Training
inferred← citeshttps://doi.org/10.1145/3645279.3645286openalex-snapshot
Research on Video Image Transmission System of Power Equipment Inspection Based on Deep Learning
inferred← citeshttps://doi.org/10.2478/amns.2023.2.01575openalex-snapshot
Research on action recognition for college dance teaching based on deep learning
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