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Deep Multi-scale Discriminative Networks for Double JPEG Compression Forensics

https://doi.org/10.1145/3301274
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-540-30114-1_10openalex-snapshot
Statistical Tools for Digital Forensics
inferredcites →https://doi.org/10.1007/978-3-642-15825-4_10openalex-snapshot
Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition
inferredcites →https://doi.org/10.1007/978-3-642-40779-6_9openalex-snapshot
Detecting Resized Double JPEG Compressed Images – Using Support Vector Machine
inferredcites →https://doi.org/10.1016/j.dsp.2015.03.014openalex-snapshot
Estimating JPEG compression history of bitmaps based on factor histogram
inferredcites →https://doi.org/10.1016/j.forsciint.2015.10.024openalex-snapshot
An improved parameter estimation scheme for image modification detection based on DCT coefficient analysis
inferredcites →https://doi.org/10.1016/j.jvcir.2017.09.003openalex-snapshot
Aligned and non-aligned double JPEG detection using convolutional neural networks
inferredcites →https://doi.org/10.1016/j.patcog.2009.03.019openalex-snapshot
Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis
inferredcites →https://doi.org/10.1016/j.patcog.2016.12.010openalex-snapshot
An approach to detecting JPEG down-recompression and seam carving forgery under recompression anti-forensics
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cvprw.2017.233openalex-snapshot
Localization of JPEG Double Compression Through Multi-domain Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/icassp.2011.5946978openalex-snapshot
Improved DCT coefficient analysis for forgery localization in JPEG images
inferredcites →https://doi.org/10.1109/ism.2011.37openalex-snapshot
Passive Forensics Method to Detect Tampering for Double JPEG Compression Image
inferredcites →https://doi.org/10.1109/ism.2012.61openalex-snapshot
An Improved Double Compression Detection Method for JPEG Image Forensics
inferredcites →https://doi.org/10.1109/lsp.2015.2438008openalex-snapshot
Median Filtering Forensics Based on Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/mmsp.2008.4665171openalex-snapshot
Detecting doubly compressed JPEG images by using Mode Based First Digit Features
inferredcites →https://doi.org/10.1109/mmsp13187.2008openalex-snapshot
2008 IEEE 10th Workshop on Multimedia Signal Processing
inferredcites →https://doi.org/10.1109/msp.2008.931079openalex-snapshot
Image forgery detection
inferredcites →https://doi.org/10.1109/tcyb.2014.2326059openalex-snapshot
Texture Classification and Retrieval Using Shearlets and Linear Regression
inferredcites →https://doi.org/10.1109/tcyb.2017.2747143openalex-snapshot
Superpixel-Based Foreground Extraction With Fast Adaptive Trimaps
inferredcites →https://doi.org/10.1109/tifs.2012.2187516openalex-snapshot
Image Forgery Localization via Block-Grained Analysis of JPEG Artifacts
inferredcites →https://doi.org/10.1109/tifs.2014.2345479openalex-snapshot
Exploring DCT Coefficient Quantization Effects for Local Tampering Detection
inferredcites →https://doi.org/10.1109/tifs.2014.2359368openalex-snapshot
An Effective Method for Detecting Double JPEG Compression With the Same Quantization Matrix
inferredcites →https://doi.org/10.1109/tifs.2015.2389148openalex-snapshot
Revealing the Trace of High-Quality JPEG Compression Through Quantization Noise Analysis
inferredcites →https://doi.org/10.1109/tifs.2016.2604208openalex-snapshot
JPEG Quantization Step Estimation and Its Applications to Digital Image Forensics
inferredcites →https://doi.org/10.1109/tifs.2016.2636089openalex-snapshot
Multi-Scale Analysis Strategies in PRNU-Based Tampering Localization
inferredcites →https://doi.org/10.1109/tip.2015.2405477openalex-snapshot
Statistical Model of JPEG Noises and Its Application in Quantization Step Estimation
inferredcites →https://doi.org/10.1109/tip.2016.2518870openalex-snapshot
Multi-Scale Fusion for Improved Localization of Malicious Tampering in Digital Images
inferredcites →https://doi.org/10.1109/tip.2016.2535273openalex-snapshot
Blind Estimation of Blur Kernels and Parameters from a Single Image
inferredcites →https://doi.org/10.1109/tip.2016.2553521openalex-snapshot
Analyzing the Effect of JPEG Compression on Local Variance of Image Intensity
inferredcites →https://doi.org/10.1109/tip.2017.2682963openalex-snapshot
Blind Forensics of Successive Geometric Transformations in Digital Images Using Spectral Method: Theory and Applications
inferredcites →https://doi.org/10.1109/tip.2017.2691802openalex-snapshot
Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal
inferredcites →https://doi.org/10.1109/tmm.2016.2571999openalex-snapshot
Audio Recapture Detection With Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/tmm.2016.2598092openalex-snapshot
A Deep Neural Network-Driven Feature Learning Method for Multi-view Facial Expression Recognition
inferredcites →https://doi.org/10.1109/tnnls.2017.2727140openalex-snapshot
Patch Alignment Manifold Matting
inferredcites →https://doi.org/10.1117/12.525375openalex-snapshot
UCID: an uncompressed color image database
inferredcites →https://doi.org/10.1117/12.704723openalex-snapshot
A generalized Benford's law for JPEG coefficients and its applications in image forensics
inferredcites →https://doi.org/10.1145/1899412.1899420openalex-snapshot
Neighboring joint density-based JPEG steganalysis
inferredcites →https://doi.org/10.1145/2560365openalex-snapshot
Improved Approaches with Calibrated Neighboring Joint Density to Steganalysis and Seam-Carved Forgery Detection in JPEG Images
inferredcites →https://doi.org/10.1145/2647868.2654889openalex-snapshot
Caffe
inferredcites →https://doi.org/10.1145/2735952openalex-snapshot
A Real-Time Hand Posture Recognition System Using Deep Neural Networks
inferredcites →https://doi.org/10.1145/2909827.2930786openalex-snapshot
A Deep Learning Approach to Universal Image Manipulation Detection Using a New Convolutional Layer
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3065951openalex-snapshot
Visual Classification of Furniture Styles
inferredcites →https://doi.org/10.1186/s13635-016-0047-yopenalex-snapshot
Double JPEG compression forensics based on a convolutional neural network
inferredcites →https://doi.org/10.5591/978-1-57735-516-8/ijcai11-210openalex-snapshot
Flexible, high performance convolutional neural networks for image classification

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s00500-020-05257-0openalex-snapshot
Visual analysis framework for network abnormal data based on multi-agent model
inferred← citeshttps://doi.org/10.1007/s11760-024-02997-6openalex-snapshot
Toward effective image forensics via a novel computationally efficient framework and a new image splice dataset
inferred← citeshttps://doi.org/10.1016/j.cose.2026.104864openalex-snapshot
A survey on JPEG image forensics: Exploring key advances and persistent challenges in compression and quantization analysis
inferred← citeshttps://doi.org/10.1016/j.dsp.2022.103429openalex-snapshot
Double JPEG compression detection and localization based on convolutional auto-encoder for image content removal
inferred← citeshttps://doi.org/10.1016/j.enganabound.2025.106290openalex-snapshot
A customized CNN architecture for detecting double and multiple JPEG compression in small blocks
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.123756openalex-snapshot
Datasets, clues and state-of-the-arts for multimedia forensics: An extensive review
inferred← citeshttps://doi.org/10.1016/j.jvcir.2021.103269openalex-snapshot
A novel deep learning framework for double JPEG compression detection of small size blocks
inferred← citeshttps://doi.org/10.1109/icct46805.2019.8947235openalex-snapshot
Localizing JPEG Image Forgeries via SIFT and DCT Coefficient Analysis
inferred← citeshttps://doi.org/10.1109/icict48043.2020.9112445openalex-snapshot
Person Sensor-Aided Scene Recognition and Understanding Based on CG Technology
inferred← citeshttps://doi.org/10.1109/jsen.2024.3411607openalex-snapshot
Spatiotemporal Interactive Pedestrian Intention Prediction With Illumination Transformation
inferred← citeshttps://doi.org/10.1109/tcsvt.2019.2959815openalex-snapshot
Feature Consistency Training With JPEG Compressed Images
inferred← citeshttps://doi.org/10.1109/tcsvt.2020.3003653openalex-snapshot
A Clustering-Based Framework for Improving the Performance of JPEG Quantization Step Estimation
inferred← citeshttps://doi.org/10.1109/tcsvt.2021.3071218openalex-snapshot
Forensic Analysis of JPEG-Domain Enhanced Images via Coefficient Likelihood Modeling
inferred← citeshttps://doi.org/10.1109/tifs.2021.3129654openalex-snapshot
Image Splicing Detection, Localization and Attribution via JPEG Primary Quantization Matrix Estimation and Clustering
inferred← citeshttps://doi.org/10.1109/tmm.2022.3217384openalex-snapshot
Vision-Language Matching for Text-to-Image Synthesis via Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1109/tnnls.2022.3165573openalex-snapshot
DR-GAN: Distribution Regularization for Text-to-Image Generation
inferred← citeshttps://doi.org/10.1111/exsy.13102openalex-snapshot
Tampering detection and localization base on sample guidance and individual camera device convolutional neural network features
inferred← citeshttps://doi.org/10.1145/3731243openalex-snapshot
Unravelling Digital Forgeries: A Systematic Survey on Image Manipulation Detection and Localization
inferred← citeshttps://doi.org/10.1609/aaai.v37i1.25095openalex-snapshot
Self-Supervised Image Local Forgery Detection by JPEG Compression Trace
inferred← citeshttps://doi.org/10.3390/s20082262openalex-snapshot
Exposing Digital Image Forgeries by Detecting Contextual Abnormality Using Convolutional Neural Networks
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