Papers Image Forgery Detection
“Image Forgery Detection” 태그가 달린 논문 47편 · 필터 해제
Training Data Improvement for Image Forgery Detection using Comprint
Manipulated images are a threat to consumers worldwide, when they are used to spread disinformation. Therefore, Comprint enables forgery detection by utilizing JPEG-compression fingerprints. This paper evaluates the impa…
Image Forgery DetectionComprint: Image Forgery Detection and Localization using Compression Fingerprints
Manipulation tools that realistically edit images are widely available, making it easy for anyone to create and spread misinformation. In an attempt to fight fake news, forgery detection and localization methods were des…
Image Forgery DetectionMisinformationMulti-Forgery Detection Challenge 2022: Push the Frontier of Unconstrained and Diverse Forgery Detection
In this paper, we present the Multi-Forgery Detection Challenge held concurrently with the IEEE Computer Society Workshop on Biometrics at CVPR 2022. Our Multi-Forgery Detection Challenge aims to detect automatic image m…
Image Forgery DetectionImage GenerationvalidImage Forgery Detection with Interpretability
In this work, we present a learning based method focusing on the convolutional neural network (CNN) architecture to detect these forgeries. We consider the detection of both copy-move forgeries and inpainting based forge…
ClassificationImage Forgery DetectionRobust Image Forgery Detection Over Online Social Network Shared Images
The increasing abuse of image editing softwares, such as Photoshop and Meitu, causes the authenticity of digital images questionable. Meanwhile, the widespread availability of online social networks (OSNs) makes them…
Image Forgery DetectionImage Manipulation DetectionAnalysing Statistical methods for Automatic Detection of Image Forgery
Image manipulation and forgery detection have been a topic of research for more than a decade now. New-age tools and large-scale social platforms have given space for manipulated media to thrive. These media can be poten…
Image Forgery DetectionImage ManipulationCopy-Move Image Forgery Detection Based on Evolving Circular Domains Coverage
The aim of this paper is to improve the accuracy of copy-move forgery detection (CMFD) in image forensics by proposing a novel scheme and the main contribution is evolving circular domains coverage (ECDC) algorithm. The …
Image ForensicsImage Forgery DetectionFFR_FD: Effective and Fast Detection of DeepFakes Based on Feature Point Defects
The internet is filled with fake face images and videos synthesized by deep generative models. These realistic DeepFakes pose a challenge to determine the authenticity of multimedia content. As countermeasures, artifact-…
DeepFake DetectionDetecting Image ManipulationFace SwappingImage Forgery DetectionForgery Blind Inspection for Detecting Manipulations of Gel Electrophoresis Images
Recently, falsified images have been found in papers involved in research misconducts. However, although there have been many image forgery detection methods, none of them was designed for molecular-biological experiment…
Image Forgery DetectionOn Addressing the Impact of ISO Speed upon PRNU and Forgery Detection
Photo Response Non-Uniformity (PRNU) has been used as a powerful device fingerprint for image forgery detection because image forgeries can be revealed by finding the absence of the PRNU in the manipulated areas. The cor…
AttributeImage Forgery DetectionSensitivityFake face detection via adaptive manipulation traces extraction network
With the proliferation of face image manipulation (FIM) techniques such as Face2Face and Deepfake, more fake face images are spreading over the internet, which brings serious challenges to public confidence. Face image f…
Face DetectionFace SwappingImage ForensicsImage Forgery Detection+1Exposing Fake Images with Forensic Similarity Graphs
We propose new image forgery detection and localization algorithms by recasting these problems as graph-based community detection problems. To do this, we introduce a novel abstract, graph-based representation of an imag…
Community DetectionImage Forgery DetectionA Full-Image Full-Resolution End-to-End-Trainable CNN Framework for Image Forgery Detection
Due to limited computational and memory resources, current deep learning models accept only rather small images in input, calling for preliminary image resizing. This is not a problem for high-level vision problems, wher…
Image ForensicsImage Forgery DetectionDesign an Advance computer-aided tool for Image Authentication and Classification
Over the years, advancements in the fields of digital image processing and artificial intelligence have been applied in solving many real-life problems. This could be seen in facial image recognition for security systems…
Image CompressionImage Forgery DetectionSmart Novel Computer-based Analytical Tool for Image Forgery Authentication
This paper presents an integration of image forgery detection with image facial recognition using black propagation neural network (BPNN). We observed that facial image recognition by itself will always give a matching o…
Image Forgery DetectionLabel Denoising Adversarial Network (LDAN) for Inverse Lighting of Faces
Lighting estimation from faces is an important task and has applications in many areas such as image editing, intrinsic image decomposition, and image forgery detection. We propose to train a deep Convolutional Neural Ne…
DenoisingImage Forgery DetectionIntrinsic Image DecompositionLighting EstimationBlind Document Image Quality Prediction Based on Modification of Quality Aware Clustering Method Integrating a Patch Selection Strategy
The quality of document images has direct impacts on the performance of document image processing systems. Document Image Quality Assessment (DIQA) is, therefore, of fundamental importance to a numerous document processi…
Document Image Quality AssessmentImage Forgery DetectionImage Quality AssessmentNo-Reference Image Quality AssessmentImage forgery detection for high resolution images using SIFT and RANSAC algorithm
Cloning (copy-move forgery) is a malicious tampering attack with digital images where a part of image is copied and pasted within the image to conceal the important details of image without any obvious traces of manip…
Image Forgery DetectionVocal Bursts Intensity PredictionSatellite Image Forgery Detection and Localization Using GAN and One-Class Classifier
Current satellite imaging technology enables shooting high-resolution pictures of the ground. As any other kind of digital images, overhead pictures can also be easily forged. However, common image forensic techniques ar…
Generative Adversarial NetworkImage Forgery DetectionOne-class classifierBoosting Image Forgery Detection using Resampling Features and Copy-move analysis
Realistic image forgeries involve a combination of splicing, resampling, cloning, region removal and other methods. While resampling detection algorithms are effective in detecting splicing and resampling, copy-move dete…
Image Forgery DetectionImage ManipulationImage Manipulation Detection