The 2021 Hotel-ID to Combat Human Trafficking Competition Dataset
This addresses the challenge of fine-grained visual classification for law enforcement and anti-trafficking efforts, though it is incremental as it focuses on dataset creation rather than a new method.
The paper tackles the problem of hotel recognition for human trafficking investigations by introducing the 2021 Hotel-ID dataset, which consists of crowd-sourced images from the TraffickCam app to help models accurately identify hotels from low-quality investigative photos.
Hotel recognition is an important task for human trafficking investigations since victims are often photographed in hotel rooms. Identifying these hotels is vital to trafficking investigations since they can help track down current and future victims who might be taken to the same places. Hotel recognition is a challenging fine grained visual classification task as there can be little similarity between different rooms within the same hotel, and high similarity between rooms from different hotels (especially if they are from the same chain). Hotel recognition to combat human trafficking poses additional challenges as investigative images are often low quality, contain uncommon camera angles and are highly occluded. Here, we present the 2021 Hotel-ID dataset to help raise awareness for this problem and generate novel approaches. The dataset consists of hotel room images that have been crowd-sourced and uploaded through the TraffickCam mobile application. The quality of these images is similar to investigative images and hence models trained on these images have good chances of accurately narrowing down on the correct hotel.