Datasets

FloreView

The dataset consists of outdoor content acquired from 46 smartphones of 11 major brands. For each device, we collected a total of 9206 media contents (6637 images and 1831 videos). Natural images and videos captured with each smartphone portray the same subjects, in order to reduce biases that could influence the performance of forensics methods.

The ‘EVA-7K dataset’ contains 7000 videos: native, altered and exchanged through social platforms. The altered contents include manipulations with FFmpeg, AVIdemux, Kdenlive and Adobe Premiere. The social platforms used to exchange the native and altered videos are Facebook, Tiktok, Youtube and Weibo. A detailed description of the dataset is available in the journal paper “Efficient Video Integrity Analysis Through Container Characterization”.

The ‘HDR dataset’ contains more than 5000 Standard Dynamic Range (SDR) and High Dynamic Range (HDR) images captured using 23 different mobile devices of 7 major brands. A detailed description of the dataset is available in the journal paper “A New Dataset for Source Identification of High Dynamic Range Images”, published on Sensors, 2018.

VISION

The ‘VISION dataset’ contains more than 35000 images and videos captured using 35 different portable devices of 11 major brands. A detailed description of the dataset is available in the scientific, open access paper “VISION: a video and image dataset for source identification”, published on EURASIP Journal on Information Security on Dec. 2017.

Errata (17/04/2019)

We regret to inform the VISION users that the following videos have been misplaced therefore we suggest to not consider them as native (and social) contents in your analysis.

  • D03_V_flat_still_0002.mp4, D03_V_flatYT_still_0002.mp4, D03_V_flatWA_still_0002.mp4
  • D19_V_flat_move_0002.mov, D19_V_flatYT_move_0002.mp4, D19_V_flatWA_move_0002.mp4

Dataset used in the experiments reported in T.Bianchi, A.Piva, “Image Forgery Localization via Block-Grained Analysis of JPEG Artifacts”, IEEE Transactions on Information Forensics & Security, vol. 7, no. 3, June 2012, pp. 1003 - 1017. This dataset by Alessandro Nozzoli is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

Image dataset for PRNU on Modern Devices

Dataset used in the experiments reported in Albisani, Chiara, Massimo Iuliani, and Alessandro Piva. “Checking PRNU Usability on Modern Devices.” ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021.