# Manipulation Detection in Satellite Images Using Vision Transformer

arXiv: https://arxiv.org/abs/2105.06373 · HTML: https://mlsanity.com/paper/2105.06373/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 May 2021.

## Built on by (most cited first, 16 of 16)

- [A Comprehensive Survey of Transformers for Computer Vision](https://mlsanity.com/paper/2211.06004/) (2022)
- [Deep learning for precipitation nowcasting: A survey from the perspective of time series forecasting](https://mlsanity.com/paper/2406.04867/) (2024)
- [An Overview of Recent Work in Media Forensics: Methods and Threats](https://mlsanity.com/paper/2204.12067/) (2022)
- [TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization](https://mlsanity.com/paper/2308.05264/) (2023)
- [Back-in-Time Diffusion: Unsupervised Detection of Medical Deepfakes](https://mlsanity.com/paper/2407.15169/) (2024)
- [An Overview on the Generation and Detection of Synthetic and Manipulated Satellite Images](https://mlsanity.com/paper/2209.08984/) (2022)
- [Amplitude SAR Imagery Splicing Localization](https://mlsanity.com/paper/2201.02409/) (2022)
- [Learning from Synthetic InSAR with Vision Transformers: The case of volcanic unrest detection](https://mlsanity.com/paper/2201.03016/) (2022)
- [A One-Class Classifier for the Detection of GAN Manipulated Multi-Spectral Satellite Images](https://mlsanity.com/paper/2305.11795/) (2023)
- [Fusion of Satellite Images and Weather Data with Transformer Networks for Downy Mildew Disease Detection](https://mlsanity.com/paper/2209.02797/) (2022)
- [Tools for Extracting Spatio-Temporal Patterns in Meteorological Image Sequences: From Feature Engineering to Attention-Based Neural Networks](https://mlsanity.com/paper/2210.12310/) (2022)
- [GAN-Based Object Removal in High-Resolution Satellite Images](https://mlsanity.com/paper/2301.11726/) (2023)
- [HRFNet: High-Resolution Forgery Network for Localizing Satellite Image Manipulation](https://mlsanity.com/paper/2307.11052/) (2023)
- [Exploring The Neural Burden In Pruned Models: An Insight Inspired By Neuroscience](https://mlsanity.com/paper/2407.16716/) (2024)
- [CrossVIT-augmented Geospatial-Intelligence Visualization System for Tracking Economic Development Dynamics](https://mlsanity.com/paper/2412.10474/) (2024)
- [Can Image Splicing and Copy-Move Forgery Be Detected by the Same Model? Forensim: An Attention-Based State-Space Approach](https://mlsanity.com/paper/2602.10079/) (2026)

## Abstract (arXiv)

A growing number of commercial satellite companies provide easily accessible satellite imagery. Overhead imagery is used by numerous industries including agriculture, forestry, natural disaster analysis, and meteorology. Satellite images, just as any other images, can be tampered with image manipulation tools. Manipulation detection methods created for images captured by "consumer cameras" tend to fail when used on satellite images due to the differences in image sensors, image acquisition, and processing. In this paper we propose an unsupervised technique that uses a Vision Transformer to detect spliced areas within satellite images. We introduce a new dataset which includes manipulated satellite images that contain spliced objects. We show that our proposed approach performs better than existing unsupervised splicing detection techniques.