4 accepted papers
Image forgery detection and localization (IFDL) is of vital importance as forged images can spread misinformation that poses potential threats to our daily life. However, previous methods still struggled to effectively handle forged images processed with diverse forgery operations in real-world scen…
Existing Text Image Forgery Localization (T-IFL) methods often suffer from poor generalization due to the limited scale of real-world datasets and the distribution gap caused by synthetic data that fails to capture the complexity of real-world tampering. To tackle this issue, we propose Fourier Seri…
As manipulating images may lead to misinterpretation of the visual content addressing the image forgery detection and localization (IFDL) problem has drawn serious public concerns. In this work we propose a simple assumption that the effective forensic method should focus on the mesoscopic propertie…
In this paper, we present the Screenshot Text Forgery Dataset (STFD), which is the first public dataset for the smartphone screenshot text forgery localization task. To address such a task, we propose a novel Screenshot Text Forgery Localization Network (STFL-Net). Specifically, we introduce the OCR…