Image Manipulation Localization
7 papers with code • 5 benchmarks • 2 datasets
The task of segmenting parts of images or image parts that have been tampered with or manipulated (sometimes also referred to as doctored). This typically encompasses image splicing, copy-move, or image inpainting.
Benchmarks
These leaderboards are used to track progress in Image Manipulation Localization
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Casia V1+
Most implemented papers
ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features
To fight against real-life image forgery, which commonly involves different types and combined manipulations, we propose a unified deep neural architecture called ManTra-Net.
Image Manipulation Detection by Multi-View Multi-Scale Supervision
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.
Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization
It significantly outperforms traditional and deep neural network-based methods in detecting and localizing tampered regions.
IML-ViT: Benchmarking Image Manipulation Localization by Vision Transformer
To bridge this gap, based on the fact that artifacts are sensitive to image resolution, amplified under multi-scale features, and massive at the manipulation border, we formulate the answer to the former question as building a ViT with high-resolution capacity, multi-scale feature extraction capability, and manipulation edge supervision that could converge with a small amount of data.
Pre-training-free Image Manipulation Localization through Non-Mutually Exclusive Contrastive Learning
knightzjz/ncl-iml
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ICCV 2023
We argue that contrastive learning is more suitable to tackle the data insufficiency problem for IML.
Exploring Multi-Modal Fusion for Image Manipulation Detection and Localization
Recent image manipulation localization and detection techniques usually leverage forensic artifacts and traces that are produced by a noise-sensitive filter, such as SRM and Bayar convolution.
