Papers Detecting Image Manipulation
“Detecting Image Manipulation” 태그가 달린 논문 12편 · 필터 해제
Digital Image Forensics: A quantitative & qualitative comparison between State-of-the-art-AI and Traditional Techniques for detection and localization of image manipulations
With the rise of realistic AI-generated images and continuously advancing photo-editing software, it has become increasingly difficult to reliably distinguish between authentic and manipulated images. Using Digital Image…
Detecting Image ManipulationImage ForensicsImage Forgery DetectionImage Manipulation+4MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization
Recent image manipulation localization and detection techniques typically leverage forensic artifacts and traces that are produced by a noise-sensitive filter, such as SRM or Bayar convolution. In this paper, we showcase…
Detecting Image ManipulationImage ForensicsImage Forgery DetectionImage Manipulation+2Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset
This residual network has been a broad domain of research in deep learning. Many complex architectures are based upon residual networks. Residual networks are efficient due to skip connections. This paper highlights the…
ClassificationData AugmentationData VisualizationDetecting Image Manipulation+14AugStatic - A Light-Weight Image Augmentation Library
The rapid exponential increase in the data led to an abrupt mix of various data types, leading to a deficiency of helpful information. Creating new data with the existing different types of data are presented in this pap…
ClassificationData AugmentationData VisualizationDetecting Image Manipulation+13Augmented Balanced Image Dataset Generator Using AugStatic Library
The mixed data consists of various structured and unstructured data. The exponential boom of the amount of data has made the datasets of varying samples. This paper focuses on the image dataset generator that balances an…
ClassificationData AugmentationData VisualizationDetecting Image Manipulation+13Improving Model Performance and Removing the Class Imbalance Problem Using Augmentation
The data in the real world consists of various kinds of painful features. A majorly found one is the class imbalance in which the number of examples in different classes in a dataset is unequal. The class imbalance is be…
ClassificationData AugmentationData VisualizationDetecting Image Manipulation+13Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset
although best-in-class AI can deliver extraordinary outcomes in experimentation, data scientists struggle to duplicate these outcomes on actual-world data. It's nothing unexpected-actual data mirrors the messy world that…
ClassificationData AugmentationData VisualizationDetecting Image Manipulation+13Deep PCB To COCO Convertor
Millions of datasets and many models use the input datasets in COCO format. In this paper, we are converting the Deep PCB dataset to COCO format. The Deep PCB is a manufacturing defect data set. It has 1500 image pairs. …
ClassificationData AugmentationData VisualizationDetecting Image Manipulation+15TAFIM: Targeted Adversarial Attacks against Facial Image Manipulations
Face manipulation methods can be misused to affect an individual's privacy or to spread disinformation. To this end, we introduce a novel data-driven approach that produces image-specific perturbations which are embedded…
DeepFake DetectionDetecting Image ManipulationImage ManipulationFFR_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 DetectionVideo Face Manipulation Detection Through Ensemble of CNNs
In the last few years, several techniques for facial manipulation in videos have been successfully developed and made available to the masses (i.e., FaceSwap, deepfake, etc.). These methods enable anyone to easily edit f…
DeepFake DetectionDetecting Image ManipulationFake Image DetectionGAN image forensics+3Generate, Segment and Refine: Towards Generic Manipulation Segmentation
Detecting manipulated images has become a significant emerging challenge. The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipula…
Detecting Image ManipulationImage GenerationImage Manipulation DetectionMisinformation+1