Image Synthesis from Yahoo’s open_nsfw

Yahoo’s recently open sourced neural network, open_nsfw, is a fine tuned Residual Network which scores images on a scale of to on its suitability for use in the workplace. In the documentation, Yahoo notes

Defining NSFW material is subjective and the task of identifying these images is non-trivial. Moreover, what may be objectionable in one context can be suitable in another.

What makes an image NSFW, according to Yahoo? I explore this question with a clever new visualization technique by Nguyen et al.. Like Google’s Deep Dream, this visualization trick works by maximally activating certain neurons of the classifier. Unlike deep dream, we optimize these activations by performing descent on a parameterization of the manifold of natural images. This parametrization takes the form of a Generative Network, , trained adversarially on an unrelated dataset of natural images.

The “space of natural images”, according to , look mostly like abstract art. Unsurprisingly, these random pictures, lacking any kind of semantics, have low scores on the classifier.