1. A computer-implemented method, comprising: obtaining multiple frames from a video, wherein each frame of the multiple frames depicts an object to be recognized; and processing, using an object recognition model, the multiple frames to generate data that represents a classification of the object to be recognized, wherein the object recognition model is a recurrent neural network that comprises a long short-term memory (LSTM) layer and multiple feature extraction layers, wherein the LSTM layer includes a convolutional input gate, a convolutional forget gate, a convolutional memory block, and a convolutional output gate that use convolutions to process data, and wherein the processing comprises, for each frame of the multiple frames: processing, using the multiple feature extraction layers, the frame to generate feature data that represents features of the frame; and processing, using the LSTM layer, the feature data to generate an LSTM output and to update an internal state of the LSTM layer.