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Post-Data Augmentation to Improve Deep Pose Estimation of Extreme and Wild Motions
[article]
2019
arXiv
pre-print
Contributions of recent deep-neural-network (DNN) based techniques have been playing a significant role in human-computer interaction (HCI) and user interface (UI) domains. One of the commonly used DNNs is human pose estimation. This kind of technique is widely used for motion capturing of humans, and to generate or modify virtual avatars. However, in order to gain accuracy and to use such systems, large and precise datasets are required for the machine learning (ML) procedure. This can be
arXiv:1902.04250v1
fatcat:njbsd6p6xzeevmn3i7vah25nqa