This is an general-purpose action recognition model for Kinetics-400 dataset. The model uses Video Transformer approach with ResNet34 encoder. Please refer to the kinetics dataset specification to see list of action that are recognised by this model.
This model is only encoder part of the whole pipeline. It accepts video frame and produces embedding. Use action-recognition-0001-decoder to produce prediction from embeddings of 16 frames. Video frames should be sampled to cover ~1 second fragment (i.e. skip every second frame in 30 fps video).
Link to performance table
name: "0" , shape: [1x3x224x224] - An input image in the format [BxCxHxW], where:
Expected color order is BGR.
The model outputs a tensor with the shape [1x512x1x1], representing embedding of precessed frame.
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