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Item: Title: Forged ID Document videos generation. Item: Title: Private Dataset. Item: Title: Data Records Item: Title: Technical Validation Children: Item: Title: Document Verification tasks. Item: Title: Usage Notes Item: Title: Acknowledgements Item: Title: Fig. 1 Crop & Replace Composite PAI example. Item: Title: Fig. 2 Inpainting Composite PAI example. Item: Title: Fig. 3 Pathflow followed to generate forged videos and clips. Item: Title: Fig. 4 Distribution of videos according to: (a) phone year of release (b) resolution of the smartphone main rear camera (in megapixels). Item: Title: Fig. 5 Examples of SIDTD video clips of fake documents with different backgrounds, lightening and devices: (a) Finnish ID Document captured with natural light with table background recorded with Xiaomi Mi Max 2 (b) Spanish ID Document captured with natura Item: Title: Fig. 6 (a) Example of folder structure corresponding to template document data after downloading it. Item: Title: Fig. 7 Example of an annotation from the MIDV2020 dataset. Item: Title: Fig. 8 Example of the annotation format for the clips extracted from the videos. Item: Title: Fig. 9 Examples of code to load the dataset in (a) Python and (b) Bash shell. Item: Title: Fig. 10 Code example to generate new fake data. Item: Title: Fig. 11 Example of code to load a pre-trained model, EfficientNet and test it onthe SIDT dartaset with, and without, GPU device. Item: Title: Table 1 Description of main metadata of annotated document images. Item: Title: Table 2 Statistics of the SIDTD dataset. Item: Title: Table 3 Fields of the CSV files generated for data partition. Item: Title: Table 4 Data partitions splits depending on the validation technique and whether the number of bona fide and forged classes are balanced, or not. Item: Title: Table 5 Performance for the Composite Detection and the Source Detection tasks for the proposed dataset. Item: Title: Table 6 Accuracy of the reference deep learning models for each PAIs technique and bona fide samples on the k-fold cross-validation and unbalanced data partition. Item: Title: Table 7 Accuracy of the reference deep learning models for each PAIs technique and bona fide samples on the few-shot and unbalanced data partition. 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