Experimental studies have shown that SkelResNet outperforms CNN-based methods in the existing literature in action recognition and transfer learning is an ...
Jul 26, 2024 · In this work, we consider a transfer learning approach based on K-means for splice site recognition. We use different representations for the ...
In this study, SkelResNet architecture is designed based on the pre-trained ResNet101 model. Four different image representations were created using skeletal ...
SkeleTR is a general framework for versatile skeleton ac- tion recognition tasks, which enables transfer learning and joint learning across different tasks.
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Sep 20, 2023 · SkeleTR works with a two-stage paradigm. It first models the intra-person skeleton dynamics for each skeleton sequence with graph convolutions.
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What is skeleton-based action recognition?
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It also enables transfer learning and joint training across different action tasks and datasets, which result in performance improvement. When evaluated on ...
There are three different methods mainly used to perform skeleton based action recognition: Convolutional Neural Networks (CNN), Recurrent Neural Networks ...
Jun 30, 2022 · We intend to recognize our small-scale fine-grained Tai Chi action dataset using neural networks and propose a transfer-learning method using NTU RGB+D dataset.
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In this paper, a knowledge distillation based light-weight deep model is proposed for skeleton human action recognition to meet the edge multimedia IoT ...
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Jul 8, 2019 · We present a new deep learning approach for real-time 3D human action recognition from skeletal data and apply it to develop a vision-based intelligent ...