1. A computer-implemented method for identifying reference content within provided content, comprising: training a convolutional neural network (CNN) to generate fingerprints using triplets of frames selected from a set of training content, wherein each of the triplets of frames includes an anchor frame, a positive frame, and a negative frame, wherein a fingerprint generated for an anchor frame of one of the triplets of frames is similar to a fingerprint generated for a positive frame of the one of the triplets of frames and dissimilar to a fingerprint generated for a negative frame of the one of the triplets of frames, wherein the negative frame of the one of the triplets of frames is selected from a first scene of the set of training content and the anchor frame of the one of the triplets of frames is selected from a second scene of the set of training content, wherein one of the fingerprints generated by training the CNN is a reference fingerprint generated from reference content representing an asset; subsequent to training the CNN, receiving provided content that may contain the asset; generating a fingerprint from the provided content using the CNN; determining whether the provided content contains the asset represented by the reference content by comparing the fingerprint generated from the provided content with the reference fingerprint; and responsive to determining that the provided content contains the asset, enforcing a policy associated with the asset on the provided content.