A computer-implemented method for determining a partition of a video into one or more chapters, the method comprising: obtaining a partition of the video into one or more shots, wherein a shot is sequence of consecutive frames with a smoothly temporally varying viewpoint; generating a fixed size feature representation of each shot, the fixed size feature representation including visual features extracted from the frames of the shot, and audio features extracted from the audio accompanying the frames of the shot, wherein generating the fixed size feature representation includes, for each particular shot: generating visual features for the particular shot, including providing video data of the particular shot as input to a visual feature neural network that processes the video data to generate one or more visual feature outputs; generating audio features for the particular shot, including providing audio data of the particular shot as input to an audio feature neural network that processes the audio data to generate one or more audio feature outputs; and generating the fixed size feature representation of the particular shot based on the visual features for the particular shot and the audio features for the particular shot; providing the fixed size feature representations of the shots as input to a partitioning recurrent neural network that is configured to process the fixed size feature representations of the shots to generate a partitioning recurrent neural network output; and determining the partition of the video into one or more chapters based on the partitioning recurrent neural network output, wherein each chapter is a sequence of consecutive shots that are determined to be taken at one or more locations depicted in the video, the consecutive shots being semantically related. obtaining a partition of the video into one or more shots, wherein a shot is sequence of consecutive frames with a smoothly temporally varying viewpoint; generating a fixed size feature representation of each shot, the fixed size feature representation including visual features extracted from the frames of the shot, and audio features extracted from the audio accompanying the frames of the shot, wherein generating the fixed size feature representation includes, for each particular shot: generating visual features for the particular shot, including providing video data of the particular shot as input to a visual feature neural network that processes the video data to generate one or more visual feature outputs; generating audio features for the particular shot, including providing audio data of the particular shot as input to an audio feature neural network that processes the audio data to generate one or more audio feature outputs; and generating the fixed size feature representation of the particular shot based on the visual features for the particular shot and the audio features for the particular shot; generating visual features for the particular shot, including providing video data of the particular shot as input to a visual feature neural network that processes the video data to generate one or more visual feature outputs; generating audio features for the particular shot, including providing audio data of the particular shot as input to an audio feature neural network that processes the audio data to generate one or more audio feature outputs; and generating the fixed size feature representation of the particular shot based on the visual features for the particular shot and the audio features for the particular shot; providing the fixed size feature representations of the shots as input to a partitioning recurrent neural network that is configured to process the fixed size feature representations of the shots to generate a partitioning recurrent neural network output; and determining the partition of the video into one or more chapters based on the partitioning recurrent neural network output, wherein each chapter is a sequence of consecutive shots that are determined to be taken at one or more locations depicted in the video, the consecutive shots being semantically related.