Copy-Move Forgery Detection and Question Answering for Remote Sensing Image

TL;DR

This paper introduces a new task, datasets, and a framework for detecting copy-move forgeries and answering questions about remote sensing images, addressing complex tampering scenarios in land monitoring and security.

Contribution

The paper presents the first RSCMQA task, multiple comprehensive datasets, and a novel multimodal forgery perception framework to improve tampering detection and question answering accuracy.

Findings

The proposed framework outperforms general VQA and RSVQA models.

Five new datasets cover diverse regions and tampering scenarios.

Public release of datasets and code facilitates future research.

Abstract

Driven by practical demands in land resource monitoring and national defense security, this paper introduces the Remote Sensing Copy-Move Question Answering (RSCMQA) task. Unlike traditional Remote Sensing Visual Question Answering (RSVQA), RSCMQA focuses on interpreting complex tampering scenarios and inferring relationships between objects. We present a suite of global RSCMQA datasets, comprising images from 29 different regions across 14 countries. Specifically, we propose five distinct datasets, including the basic dataset RS-CMQA, the category-balanced dataset RS-CMQA-B, the high-authenticity dataset Real-RSCM, the extended dataset RS-TQA, and the extended category-balanced dataset RS-TQA-B. These datasets fill a critical gap in the field while ensuring comprehensiveness, balance, and challenge. Furthermore, we introduce a region-discrimination-guided multimodal copy-move forgery perception framework (CMFPF), which enhances the accuracy of answering questions about tampered images by leveraging prompt about the differences and connections between the source and tampered domains. Extensive experiments demonstrate that our method provides a stronger benchmark for RSCMQA compared to general VQA and RSVQA models. Our datasets and code are publicly available at https://github.com/shenyedepisa/RSCMQA.