Browse State-of-the-Art › Image Manipulation Detection
Image Manipulation Detection
38 papers with code · 21 benchmarks · 16 datasets archive 2025-07-28
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.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
21 leaderboard tables shown for this task, 21 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 21 until expanded.
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
16 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 38 papers with code (73 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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16 Apr 2020 3 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)In this paper, we tackle the problem of face manipulation detection in video sequences targeting modern facial manipulation techniques.
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1 Jun 2019 3 repositories listedTo fight against real-life image forgery, which commonly involves different types and combined manipulations, we propose a unified deep neural architecture called ManTra-Net.
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29 May 2023 2 repositories listedWe 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).
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1 May 2022 2 repositories listedIt has 1500 image pairs.
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16 Dec 2021 2 repositories listedAs both clues are meant to be semantic-agnostic, the learned features are thus generalizable.
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14 Apr 2021 2 repositories listed Syntology ran 9 of 13 samples · 4 unverified · 13 pointer-only (licence)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.
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13 Jun 2019 2 repositories listed Syntology ran 1 of 10 samples · 9 unverifiedMost malicious photo manipulations are created using standard image editing tools, such as Adobe Photoshop.
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13 May 2018 2 repositories listed Syntology ran 3 of 8 samples · 5 unverifiedImage 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.
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16 May 2025 1 repository listedThe field of Fake Image Detection and Localization (FIDL) is highly fragmented, encompassing four domains: deepfake detection (Deepfake), image manipulation detection and localization (IMDL), artificial…
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29 Nov 2024 1 repository listedMoreover, we construct the ForgeryAnalysis dataset through the Chain-of-Clues prompt, which includes analysis and reasoning text to upgrade the image manipulation detection task.
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1 Sep 2024 1 repository listedUsing Digital Image Forensics, the primary objective of this work is to conduct a comprehensive quantitative and qualitative study that compares traditional forensic techniques to a state-of-the-art AI based approach.
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7 Aug 2024 1 repository listedThe MMFusion-IML baseline achieves 0.
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27 Jul 2024 1 repository listedAccordingly, in this work, we propose to detect misinformation by learning manipulation features that indicate whether the image has been manipulated, as well as intention features regarding the harmful and harmless…
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24 Jun 2024 1 repository listedThe extraordinary ability of generative models emerges as a new trend in image editing and generating realistic images, posing a serious threat to the trustworthiness of multimedia data and driving the research of image…
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15 Jun 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)A comprehensive benchmark is yet to be established in the Image Manipulation Detection & Localization (IMDL) field.
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4 May 2024 1 repository listedSeparate image forensics methods have also been developed to detect these traces.
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3 Apr 2024 1 repository listedUnlike other automated data generation frameworks, we use state of the art image composition deep learning models to generate spliced images close to the quality of real-life manipulations.
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12 Feb 2024 1 repository listedThe social media-fuelled explosion of fake news and misinformation supported by tampered images has led to growth in the development of models and datasets for image manipulation detection.
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4 Dec 2023 1 repository listedRecent 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.
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23 Nov 2023 1 repository listedExisting Image Manipulation Detection (IMD) methods are mainly based on detecting anomalous features arisen from image editing or double compression artifacts.
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3 Sep 2023 1 repository listed Syntology ran 1 of 2 samples · 1 unverifiedTo improve the generalization ability, we propose weakly-supervised self-consistency learning (WSCL) to leverage the weakly annotated images.
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19 Jun 2023 1 repository listed Syntology ran 2 of 5 samples · 3 unverified3D sensing for monocular in-the-wild images, e.
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20 Mar 2023 1 repository listed Syntology ran 4 of 4 samples · 0 unverifiedDifferent from the previous visual prompting which is typically a dataset-level implicit embedding, our key insight is to enforce the tunable parameters focusing on the explicit visual content from each individual…
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16 Oct 2022 1 repository listedMost existing methods mainly focus on extracting global features from tampered images, while neglecting the relationships of local features between tampered and authentic regions within a single tampered image.
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2 Jul 2022 1 repository listedIn this paper, the noise image extracted by the improved constrained convolution is used as the input of the model instead of the original image to obtain more subtle traces of manipulation.
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1 May 2022 1 repository listedAugStatic is a custom-built image augmentation library with lower computation costs and more extraordinary salient features compared to other image augmentation libraries.
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1 May 2022 1 repository listedThis paper focuses on the image dataset generator that balances an imbalanced dataset using the AugStatic augmentation library.
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29 Mar 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedThat is, a template protected real image, and its manipulated version, is better discriminated compared to the original real image vs.
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1 Jan 2022 1 repository listedTo fight against the OSN-shared forgeries, in this work, a novel robust training scheme is proposed.
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30 Aug 2021 1 repository listedIt significantly outperforms traditional and deep neural network-based methods in detecting and localizing tampered regions.
Syntology lines on 9 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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