Comprehensive Dataset of Synthetic and Manipulated Overhead Imagery for
  Development and Evaluation of Forensic Tools
Brandon B. May Kirill Trapeznikov Shengbang Fang Matthew C. Stamm
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.