1. A video classification method comprising: with at least one processor: receiving an input video comprising a sequence of frames; generating at least one transformation of the input video, each transformation comprising a sequence of frames; for the input video and each transformation, extracting local descriptors from the respective sequence of frames; aggregating the local descriptors of the input video and each transformation to form an aggregated feature vector with a first set of processing layers learned using unsupervised learning; and generating an output classification value for the input video based on the aggregated feature vector with a second set of processing layers learned using supervised learning.