video-classification-3d-cnn-pytorch - Video classification tools using 3D ResNet

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This is a pytorch code for video (action) classification using 3D ResNet trained by this code. The 3D ResNet is trained on the Kinetics dataset, which includes 400 action classes. This code uses videos as inputs and outputs class names and predicted class scores for each 16 frames in the score mode. In the feature mode, this code outputs features of 512 dims (after global average pooling) for each 16 frames. Torch (Lua) version of this code is available here.



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