Synthetic Data Augmentation for Video Action Classification Using Unity

Synthetic Data Augmentation for Video Action Classification Using Unity

In video analysis, collection and labeling of data can be time and resource-consuming. To solve the scarcity of data problems, synthetic data augmentation is a promising solution. In this paper, we present an approach to generate synthetic videos for action recognition using Unity, the popular game...

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Bibliographic Details
Main Authors: Nino Cauli, Diego Reforgiato Recupero
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Data augmentation
action recognition
convolutional neural networks
video transformers
synthetic video generation
Online Access:https://ieeexplore.ieee.org/document/10731852/

Internet

https://ieeexplore.ieee.org/document/10731852/

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