The following links are available only via Mozilla Firefox as
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). The natural images and videos captured with each
smartphone portray the same subjects, in order to reduce biases that could
influence the performance of the analysis methods.
The complete dataset will be released as soon as the review process of the corresponding manuscript is finalised.
'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",
published on IEEE Journal of Selected Topics in Signal
'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.
If you download and use contents of the 'HDR dataset' you
agree to the following HDR license agreement. We are pleased
to receive electronic copies of any publication making use of
our database and to add your reference to the list of related
'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 acess paper "VISION:
a video and image dataset for source identification",
published on EURASIP Journal on Information Security on Dec.
2017, freely available at this url:
If you download and use contents of the 'VISION dataset' you
agree to the following VISION license agreement. We are
pleased to receive electronic copies of any publication making
use of our database and to add your reference to the list of
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.
- D19_V_flat_move_0002.mov, D19_V_flatYT_move_0002.mp4,
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.
Image dataset for localization of double JPEG compression by
Alessandro Nozzoli, Università di Firenze is licensed under a
Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
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.