Paper Info
Title
LEARNING DOUBLE-COMPRESSION VIDEO FINGERPRINTS LEFT FROM SOCIAL-MEDIA PLATFORMS
Abstract
Social media and messaging apps have become major communication platforms. Multimedia contents promote improved user engagement and have thus become a very important communication tool. However, fake news and manipulated content can easily go viral, so, being able to verify the source of videos and images as well as to distinguish between native and downloaded content becomes essential. Most of the work performed so far on social media provenance has concentrated on images; in this paper, we propose a CNN architecture that analyzes video content to trace videos back to their social network of origin. The experiments demonstrate that stating platform provenance is possible for videos as well as images with very good accuracy.
Year
DOI
Venue
2021
10.1109/ICASSP39728.2021.9413366
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
Keywords
DocType
ISSN
Social networks, video forensics, deep learning, multitask learning, platform provenance analysis
Conference
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Irene Amerini122.38
Aris Anagnostopoulos2105467.08
Luca Maiano301.35
Lorenzo Ricciardi Celsi4176.17