Image Manipulation Detection

14 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

Learning Rich Features for Image Manipulation Detection

LarryJiang134/Image_manipulation_detection CVPR 2018

Image manipulation detection is different from traditional semantic object detection because it pays more attention to tampering artifacts than to image content, which suggests that richer features need to be learned.

Detecting Photoshopped Faces by Scripting Photoshop

PeterWang512/FALdetector ICCV 2019

Most malicious photo manipulations are created using standard image editing tools, such as Adobe Photoshop.

Video Face Manipulation Detection Through Ensemble of CNNs

polimi-ispl/icpr2020dfdc 16 Apr 2020

In this paper, we tackle the problem of face manipulation detection in video sequences targeting modern facial manipulation techniques.

Generate, Segment and Refine: Towards Generic Manipulation Segmentation

pengzhou1108/GSRNet 24 Nov 2018

The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipulated images being shared on the internet.

Content Authentication for Neural Imaging Pipelines: End-to-end Optimization of Photo Provenance in Complex Distribution Channels

pkorus/neural-imaging CVPR 2019

Forensic analysis of digital photo provenance relies on intrinsic traces left in the photograph at the time of its acquisition.

Neural Imaging Pipelines - the Scourge or Hope of Forensics?

pkorus/neural-imaging 27 Feb 2019

This paper explores end-to-end optimization of the entire image acquisition and distribution workflow to facilitate reliable forensic analysis at the end of the distribution channel, where state-of-the-art forensic techniques fail.

Localization of Deep Inpainting Using High-Pass Fully Convolutional Network

lihaod/Deep_inpainting_localization ICCV 2019

The proposed method employs a fully convolutional network that is based on high-pass filtered image residuals.

Effectiveness of random deep feature selection for securing image manipulation detectors against adversarial examples

ehsannowroozi/RDFS 25 Oct 2019

We investigate if the random feature selection approach proposed in [1] to improve the robustness of forensic detectors to targeted attacks, can be extended to detectors based on deep learning features.

PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localization

proteus1991/pscc-net 19 Mar 2021

To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to detect and localize image manipulations.

Image Manipulation Detection by Multi-View Multi-Scale Supervision

dong03/MVSS-Net ICCV 2021

The key challenge of image manipulation detection is how to learn generalizable features that are sensitive to manipulations in novel data, whilst specific to prevent false alarms on authentic images.