I wonder if it is a good idea to train a multi-label model on a single-labelled data set (using e.g. BCELoss). Is this likely to generalize well to images with multiple of the categories present? Even more important, possibly: would such a model be likely to respond correctly if no category is present?
Has anyone tried this?