MIDV-Copy

MIDV-Copy is a dataset designed for document presentation attacks detection task. It consists of three image classes: 1000 photographs of original documents, 1000 scans of original documents, and 1000 photocopies with a visible paper frame. Photographs and scans of original documents correspond to the "photo" and "scan_rotated" directories from the MIDV-2020 dataset (https://zenodo.org/records/18786808). Photocopies of documents are new data produced with printing source scans in both grayscale and color and then capturing printed documents on 5 mobile cameras. The markup contains document quadrilaterals, as well as paper quadrilaterals for photocopy images. The document image numbering is preserved across classes. The dataset is published in: L. Tolstenko, A. Bursikov, I. Kunina "Detection of photocopied documents in remote identity verification by presence of the paper frame", Proc. SPIE 14114, Eighteenth International Conference on Machine Vision (ICMV 2025), 141142E (25 Feb 2026); https://doi.org/10.1117/12.3096443