Investigations of sex trafficking sometimes have access to photographs of victims in hotel rooms. These images directly link victims to places, which can help verify where victims have been trafficked or where traffickers might operate in the future. Current machine learning approaches give promising results in image search to find the matching hotel. This paper explores approaches to make this end-to-end system better support government and law enforcement requirements, including improved performance, visualization approaches that explain what parts of the image led to a match, and infrastructure to support exporting the results of a query.

AI is the latest recruit in the ongoing efforts to stamp out the scourge of human trafficking – by helping police figure out which hotels victims are being held. Hundreds of thousands of people are shuttled across borders every year against their will and exploited, most of them young women coerced into prostitution. Traffickers often take photos of their victims in hotel rooms to use in online escort ads. Now, boffins are trying to use machine-learning software to help cops and non-profits identify where these victims are being held based on patterns discerned from the ad images. A group of researchers from George Washington University, Temple University, and Adobe in the US have built a large dataset containing over a million images from 50,000 hotels across different countries.