P-HAR: Pornographic Human Action Recognition

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Human action recognition has emerged as an active area of research within the deep learning community. The primary objective involves identifying and categorizing human actions in videos by utilizing multiple input streams, such as video and audio data. The most effective models in terms of performance include transformer-based architectures for the RGB stream, PoseC3D for the skeleton stream, and ResNet101 for the audio stream.