Three-dimensional convolutional neural networks for video highlight detection

摘要

A three-dimensional convolutional neural network may include a preliminary layer group, one or more intermediate layer groups, a final layer group, and/or other layers/layer groups. The preliminary layer group may include an input layer, a preliminary three-dimensional padding layer, a preliminary three-dimensional convolution layer, a preliminary activation layer, a preliminary normalization layer, and a preliminary downsampling layer. One or more intermediate layer groups may include an intermediate three-dimensional squeeze layer, a first intermediate normalization layer, an intermediate three-dimensional padding layer, a first intermediate three-dimensional expand layer, a second intermediate three-dimensional expand layer, an intermediate concatenation layer, a second intermediate normalization layer, an intermediate activation layer, and an intermediate combination layer. The final layer group may include a final dropout layer, a final three-dimensional convolution layer, a final activation layer, a final normalization layer, a final three-dimensional downsampling layer, and a final flatten layer.