We present a first of its kind dataset of overhead imagery for development and evaluation of forensic tools. Our dataset consists of real, fully synthetic and partially manipulated overhead imagery generated from a custom diffusion model trained on two sets of different zoom levels and on two sources of pristine data. We developed our model to support controllable generation of
multiple manipulation categories including fully synthetic imagery conditioned on real and generated base maps, and location. We also support partial in-painted imagery with same conditioning options and with several types of manipulated content. The data consist of raw images and ground truth annotations describing the manipulation parameters. We also report benchmark performance on several tasks supported by our dataset including detection of fully and partially manipulated imagery, manipulation localization and classification.
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Details
Title
Comprehensive Dataset of Synthetic and Manipulated Overhead Imagery for Development and Evaluation of Forensic Tools
Creators
Brandon B May - Systems and Technology Research
Kirill Trapeznikov - Systems and Technology Research
Shengbang Fang - Drexel University
Matthew C Stamm - Drexel University
Publication Details
ArXiv.org
Resource Type
Preprint
Language
English
Academic Unit
Electrical and Computer Engineering
Other Identifier
991020517072104721
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