Synthetic dataset of ID and Travel Document
Carlos Boned Maxime Talarmain Nabil Ghanmi Guillaume Chiron Sanket Biswas Ahmad Montaser Awal Oriol Ramos Terrades
This paper presents a new synthetic dataset of ID and travel documents,
called SIDTD. The SIDTD dataset is created to help training and evaluating
forged ID documents detection systems. Such a dataset has become a necessity as
ID documents contain personal information and a public dataset of real
documents can not be released. Moreover, forged documents are scarce, compared
to legit ones, and the way they are generated varies from one fraudster to
another resulting in a class of high intra-variability. In this paper we
trained state-of-the-art models on this dataset and we compare them to the
performance achieved in larger, but private, datasets. The creation of this
dataset will help to document image analysis community to progress in the task
of ID document verification.