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2D Pose Estimation based Child Action Recognition

arXiv 2212.09027 ↗First posted 18 Dec 2022cs.CV cs.LGcited by 0

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Abstract (arXiv)

We present a graph convolutional network with 2D pose estimation for the first time on child action recognition task achieving on par results with an RGB modality based model on a novel benchmark dataset containing unconstrained environment based videos.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 31 references that are in the map. First posted on arXiv 18 Dec 2022.

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11 of 31 references.

References · 11

  1. 2017The Kinetics Human Action Video Datasetcited by 1,894
  2. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,199
  3. 2016Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,061
  4. 2016NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysiscited by 683
  5. 2014Long-term Recurrent Convolutional Networks for Visual Recognition and Descriptioncited by 483
  6. 2018A Short Note about Kinetics-600cited by 331
  7. 2021Revisiting Skeleton-based Action Recognitioncited by 256
  8. 2020BlazePose: On-device Real-time Body Pose trackingcited by 112
  9. 2017Interpretable 3D Human Action Analysis with Temporal Convolutional Networkscited by 88
  10. 2015Differential Recurrent Neural Networks for Action Recognitioncited by 39
  11. 2018Glimpse Clouds: Human Activity Recognition from Unstructured Feature Pointscited by 33

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