Document Liveness Challenge (DLC-2021) - part 3 (cc)
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下载链接：
https://zenodo.org/record/6466763
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资源简介：
Dataset DLC-2021 consists of 1424 video clips captured in a wide range of real-world conditions and focused on ID document forensics tasks. Each clip was shot vertically and was at least 5 seconds long. Frames extracted at 10 frames per second and for the 50 first extracted frames document position is manually annotated.
The novelty of the dataset is that it contains shots from video with color laminated mock ID documents, color unlaminated copies, grayscale unlaminated copies, and screen recaptures of the documents. The proposed dataset complies with the GDPR because it contains images of synthetic IDs with generated owner photos and artificial personal information.
Part 1 contains videos, frames and markup for “original” laminated documents from MIDV-2020 collection and unlaminated gray copies.
Part 2 contains videos, frames and markup for documents recaptured from device screen
Part 3 contains videos, frames and markup for unlaminated color copies.
Share and Cite
MDPI and ACS Style
Polevoy, D.V.; Sigareva, I.V.; Ershova, D.M.; Arlazarov, V.V.; Nikolaev, D.P.; Ming, Z.; Luqman, M.M.; Burie, J.-C. Document Liveness Challenge Dataset (DLC-2021). J. Imaging 2022, 8, 181. https://doi.org/10.3390/jimaging8070181
AMA Style
Polevoy DV, Sigareva IV, Ershova DM, Arlazarov VV, Nikolaev DP, Ming Z, Luqman MM, Burie J-C. Document Liveness Challenge Dataset (DLC-2021). Journal of Imaging. 2022; 8(7):181. https://doi.org/10.3390/jimaging8070181
Chicago/Turabian Style
Polevoy, Dmitry V., Irina V. Sigareva, Daria M. Ershova, Vladimir V. Arlazarov, Dmitry P. Nikolaev, Zuheng Ming, Muhammad M. Luqman, and Jean-Christophe Burie. 2022. "Document Liveness Challenge Dataset (DLC-2021)" Journal of Imaging 8, no. 7: 181. https://doi.org/10.3390/jimaging8070181
创建时间：
2022-12-21
