1. A depth detection apparatus comprising: a memory storing raw time-of-flight sensor data received from a time-of-flight sensor; and a processor comprising a trained machine learning component having been trained using training data pairs, a training data pair comprising at least one simulated raw time-of-flight sensor frame and a corresponding simulated ground truth depth map; the trained machine learning component configured to compute in a single stage, for an item of the stored raw time-of-flight sensor data, a depth map of a surface depicted by the item, by pushing the item through the trained machine learning component.
14. The apparatus of claim 1 where the trained machine learning component is a convolutional neural network and where each training data pair comprises a frame of simulated raw time-of-flight sensor data and a ground truth depth map.