Image Manipulation Detection

21 papers with code • 1 benchmarks • 1 datasets

The task of detecting images or image parts that have been tampered or manipulated (sometimes also referred to as doctored). This typically encompasses image splicing, copy-move, or image inpainting.


Use these libraries to find Image Manipulation Detection models and implementations


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.

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.

MVSS-Net: Multi-View Multi-Scale Supervised Networks for Image Manipulation Detection

dong03/MVSS-Net 16 Dec 2021

As both clues are meant to be semantic-agnostic, the learned features are thus generalizable.

Explicit Visual Prompting for Universal Foreground Segmentations

nifangbaage/explicit-visual-prompt 29 May 2023

We take inspiration from the widely-used pre-training and then prompt tuning protocols in NLP and propose a new visual prompting model, named Explicit Visual Prompting (EVP).

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.