1. A method comprising: receiving an input image; generating a convolutional feature map; identifying, by a first type of neural network, a candidate object in the input image; determining, by a second type of neural network, a category of the candidate object; and assigning a confidence score to the category of the candidate object, wherein the first type of neural network comprises a translation invariant component configured to: classify an anchor based on overlap with a ground-truth box; and predict a shift and a scale of the anchor.