Abstract: 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.