18 papers · ranked by Valyu relevance
Youqi Wang, Shunquan Tan, R. C. Peng, Bin Li + 1 more
The increasing accessibility of image editing tools and generative AI has led to a proliferation of visually convincing forgeries, compromising the authenticity of digital media. In this paper, in addition to leveraging distortions from conventional forgeries, we repurpose the mechanism of a state-of-the-art (SOTA)…
Jianhua Yang, Anjun Xie, Tao Mai, Yifang Chen + 1 more
Image forgery localization is critical in defending against the malicious manipulation of image content, and is attracting increasing attention worldwide. In this paper, we propose a Dual-domain Fusion Swin Transformer U-Net (DFST-UNet) for image forgery localization. DFST-UNet is built on a U-shaped encoder-decoder…
Hongwei Yao, Ming Xu, Tong Qiao, Yiming Wu + 1 more
Moving away from hand-crafted feature extraction, the use of data-driven convolution neural network (CNN)-based algorithms facilitates the realization of end-to-end automated forgery detection in multimedia forensics. On the basis of fingerprints acquired by images from different camera models, the goal of this paper…
Zijie Lou, Gang Cao, Kun Guo, Haochen Zhu + 1 more
Localization Authors: ['Zijie Lou' 'Gang Cao' 'Kun Guo' 'Haochen Zhu' 'Lifang Yu'] Image forgery localization, which aims to segment tampered regions in an image, is a fundamental yet challenging digital forensic task. While some deep learning-based forensic methods have achieved impressive results, they directly learn…
Soumyaroop Nandi, Prem Natarajan, Wael AbdAlmageed
The evaluation datasets and metrics for image manipulation detection and localization (IMDL) research have been standardized. But the training dataset for such a task is still nonstandard. Previous researchers have used unconventional and deviating datasets to train neural networks for detecting image forgeries and…
S. Murali
Digital Photo images are everywhere, on the covers of magazines, in newspapers, in courtrooms, and all over the Internet. We are exposed to them throughout the day and most of the time. Ease with which images can be manipulated; we need to be aware that seeing does not always imply believing. We propose methodologies…
Ivan Castillo Camacho, Kai Wang, Irene Amerini
Seeing is not believing anymore. Different techniques have brought to our fingertips the ability to modify an image. As the difficulty of using such techniques decreases, lowering the necessity of specialized knowledge has been the focus for companies who create and sell these tools. Furthermore, image forgeries are…
Davide Cozzolino, Diego Gragnaniello, Luisa Verdoliva
—Image forgery localization is a very active and open research field for the difficulty to handle the large variety of manipulations a malicious user can perform by means of more and more sophisticated image editing tools. Here, we propose a localization framework based on the fusion of three very different tools…
Hannes Mareen, Louis De Neve, Peter Lambert, Glenn Van Wallendael + 4 more
'Benedetta Tondi' 'Irene Amerini' 'Andrea Costanzo' 'Minoru Kuribayashi'] Image manipulation is easier than ever, often facilitated using accessible AI-based tools. This poses significant risks when used to disseminate disinformation, false evidence, or fraud, which highlights the need for image forgery detection and…
Abhishek Kumar Kashyap, Rajesh Singh Parmar, Megha Agarwal, Hariom Gupta
'Hariom Gupta'] Abstract—With the headway of the advanced image handling software and altering tools, a computerized picture can be effectively controlled. The identification of image manipulation is vital in light of the fact that an image can be utilized as legitimate confirmation, in crime scene investigation, and…
Haochen Zhu, Gang Cao, Mo Zhao, Huawei Tian + 1 more
—With the widespread use of powerful image editing tools, image tampering becomes easy and realistic. Existing image forensic methods still face challenges of low generalization performance and robustness. In this letter, we propose an effective image tampering localization scheme based on ConvNeXt network and…
Sheng Qin, Ce Liang, Yuling Luo, Junxiu Liu + 2 more
When maliciously tampered images are disseminated in the media, they can potentially cause adverse effects and even jeopardize national security. Therefore, it is necessary to investigate effective methods to detect tampered images. As a challenging task, the localization of image splicing tampering investigates…
Ahmad M. Nagm, Mohamed Torky, Mohammed Mahmoud Abo Ghazala, Hosam Eldin Fawzan Sayed
'Hosam Eldin Fawzan Sayed'] Abstract. Due to the widespread of advanced digital imaging devices, forgery of digital images became more serious attack patterns. In this attack scenario, the attacker tries to manipulate the digital image to conceal some meaningful information of the genuine image for malicious purposes.…
Igor Kaltashov, Kenyon Kowalski, Ryan Sullivan, Alyssa Marsico + 1 more
Forensics has long been viewed by chemical educators as a field with great potential as far as providing inspiration for modifying chemistry laboratory curriculum and enhancing students’ learning experience at different levels. While most experiments are based on adaptation of laboratory procedures routinely used in…
Jiacheng Sun, Bingrui Li, Raghu Kalluri
Integrity of scientific data is critical in biomedical research, where images often serve as primary evidence for experimental observations and conclusions. Advances in image-editing technologies and generative artificial intelligence (AI) have increased the accessibility and realism of visual manipulation, making…
Richard J. Marsh, Ishan Costello, Mark-Alexander Gorey, Donghan Ma + 4 more
Assessing the quality of localization microscopy images is highly challenging due to difficulty in reliably detecting errors in experimental data, with artificial sharpening being a particularly common failure mode of the technique. Here we use Haar wavelet kernel analysis (HAWK), a localization microscopy data…
Ingo Fruend, Elee Stalker
Humans are remarkably well tuned to the statistical properties of natural images. However, quantitative characterization of processing within the domain of natural images has been difficult because most parametric manipulations of a natural image make that image appear less natural. We used generative adversarial…
Joerg Schnitzbauer, Yina Wang, Matthew Bakalar, Baohui Chen + 3 more
Super-resolution images reconstructed from single-molecule localizations can reveal cellular structures close to the macromolecular scale and are now being used routinely in many biomedical research applications. However, because of their coordinate-based representation, a widely applicable and unified analysis…