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Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models
With this model we generate a diverse, realistic, and physically plausible dataset of human action videos, called PHAV for "Procedural Human Action Videos".
Procedural Generation of Videos to Train Deep Action Recognition Networks
Deep learning for human action recognition in videos is making significant progress, but is slowed down by its dependency on expensive manual labeling of large video collections.
Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition
Action recognition in videos is a challenging task due to the complexity of the spatio-temporal patterns to model and the difficulty to acquire and learn on large quantities of video data.
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