TL;DR
This paper introduces a scalable, end-to-end image provenance analysis pipeline that identifies original images and transformation sequences, aiding fact-checking and authorship verification in the context of media manipulation.
Contribution
It presents a novel, scalable processing pipeline with custom image filtering and provenance graph techniques, along with a new real-world dataset from Reddit.
Findings
Outperforms state-of-the-art methods on existing datasets
Demonstrates effectiveness on real-world social media images
Provides baseline results on a new Reddit provenance dataset
Abstract
Prior art has shown it is possible to estimate, through image processing and computer vision techniques, the types and parameters of transformations that have been applied to the content of individual images to obtain new images. Given a large corpus of images and a query image, an interesting further step is to retrieve the set of original images whose content is present in the query image, as well as the detailed sequences of transformations that yield the query image given the original images. This is a problem that recently has received the name of image provenance analysis. In these times of public media manipulation ( e.g., fake news and meme sharing), obtaining the history of image transformations is relevant for fact checking and authorship verification, among many other applications. This article presents an end-to-end processing pipeline for image provenance analysis, which…
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