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Found 38 papers, 15 papers with code
FairSSD: Understanding Bias in Synthetic Speech Detectors
In this work, we examine bias in existing synthetic speech detectors to determine if they will unfairly target a particular gender, age and accent group.
Back to the Future: GNN-based NO$_2$ Forecasting via Future Covariates
Remarkably, we find that conditioning on future weather information has a greater impact than considering past traffic conditions.
Spectrogram-Based Detection of Auto-Tuned Vocals in Music Recordings
In the domain of music production and audio processing, the implementation of automatic pitch correction of the singing voice, also known as Auto-Tune, has significantly transformed the landscape of vocal performance.
Compression Robust Synthetic Speech Detection Using Patched Spectrogram Transformer
We evaluate the detection performance of PS3DT on ASVspoof2019 dataset.
All-for-One and One-For-All: Deep learning-based feature fusion for Synthetic Speech Detection
Recent advances in deep learning and computer vision have made the synthesis and counterfeiting of multimedia content more accessible than ever, leading to possible threats and dangers from malicious users.
Super-Resolution of BVOC Emission Maps Via Domain Adaptation
In our work, we aim at super-resolving low resolution emission maps derived from satellite observations by leveraging the information of emission maps obtained through numerical simulations.
Multi-BVOC Super-Resolution Exploiting Compounds Inter-Connection
In this work, we propose a strategy to super-resolve coarse BVOC emission maps by simultaneously exploiting the contributions of different compounds.
DSVAE: Interpretable Disentangled Representation for Synthetic Speech Detection
We also visualize the representation obtained from DSVAE for 17 different speech synthesizers and verify that they are indeed interpretable and discriminate bona fide and synthetic speech from each of the synthesizers.
Super-Resolution of BVOC Maps by Adapting Deep Learning Methods
Biogenic Volatile Organic Compounds (BVOCs) play a critical role in biosphere-atmosphere interactions, being a key factor in the physical and chemical properties of the atmosphere and climate.
Combining Automatic Speaker Verification and Prosody Analysis for Synthetic Speech Detection
The rapid spread of media content synthesis technology and the potentially damaging impact of audio and video deepfakes on people's lives have raised the need to implement systems able to detect these forgeries automatically.
H4VDM: H.264 Video Device Matching
We denote our proposed technique as H. 264 Video Device Matching (H4VDM).
An Overview on the Generation and Detection of Synthetic and Manipulated Satellite Images
While we focus mostly on forensic techniques explicitly tailored to the detection of AI-generated synthetic contents, we also review some methods designed for general splicing detection, which can in principle also be used to spot AI manipulate images
Speaker-Independent Microphone Identification in Noisy Conditions
This work proposes a method for source device identification from speech recordings that applies neural-network-based denoising, to mitigate the impact of counter-forensics attacks using noise injection.
Splicing Detection and Localization In Satellite Imagery Using Conditional GANs
In this paper, we describe the use of a Conditional Generative Adversarial Network (cGAN) to identify the presence of such spliced forgeries within satellite images.
Detecting GAN-generated Images by Orthogonal Training of Multiple CNNs
For this reason, detecting if an image is an actual photograph or has been synthetically generated is becoming an urgent necessity.
Amplitude SAR Imagery Splicing Localization
Synthetic Aperture Radar (SAR) images are a valuable asset for a wide variety of tasks.
Forensic Analysis of Synthetically Generated Western Blot Images
As a matter of fact, the generation of synthetic content is not restricted to multimedia data like videos, photographs or audio sequences, but covers a significantly vast area that can include biological images as well, such as western blot and microscopic images.
Forensic Analysis of Video Files Using Metadata
Such manipulations can leave traces in the metadata embedded in video files.
What's wrong with this video? Comparing Explainers for Deepfake Detection
Deepfakes are computer manipulated videos where the face of an individual has been replaced with that of another.
Anti-Aliasing Add-On for Deep Prior Seismic Data Interpolation
Data interpolation is a fundamental step in any seismic processing workflow.
DIPPAS: A Deep Image Prior PRNU Anonymization Scheme
A typical trace exploited for source device identification is the Photo Response Non-Uniformity (PRNU), a noise pattern left by the device on the acquired images.
Training Strategies and Data Augmentations in CNN-based DeepFake Video Detection
The fast and continuous growth in number and quality of deepfake videos calls for the development of reliable detection systems capable of automatically warning users on social media and on the Internet about the potential untruthfulness of such contents.
Training CNNs in Presence of JPEG Compression: Multimedia Forensics vs Computer Vision
In this work, we focus on the effect that JPEG has on CNN training considering different computer vision and forensic image classification problems.
FOCAL: A Forgery Localization Framework based on Video Coding Self-Consistency
Forgery operations on video contents are nowadays within the reach of anyone, thanks to the availability of powerful and user-friendly editing software.
A Modified Fourier-Mellin Approach for Source Device Identification on Stabilized Videos
To decide whether a digital video has been captured by a given device, multimedia forensic tools usually exploit characteristic noise traces left by the camera sensor on the acquired frames.
On the use of Benford's law to detect GAN-generated images
The advent of Generative Adversarial Network (GAN) architectures has given anyone the ability of generating incredibly realistic synthetic imagery.
Video Face Manipulation Detection Through Ensemble of CNNs
In this paper, we tackle the problem of face manipulation detection in video sequences targeting modern facial manipulation techniques.
Ranked #1 on
DeepFake Detection
on FaceForensics++
(using extra training data)
CNN-based fast source device identification
Source identification is an important topic in image forensics, since it allows to trace back the origin of an image.
We Need No Pixels: Video Manipulation Detection Using Stream Descriptors
Manipulating video content is easier than ever.
An In-Depth Study on Open-Set Camera Model Identification
To deal with this issue, in this paper, we present the first in-depth study on the possibility of solving the camera model identification problem in open-set scenarios.
Interpolation and Denoising of Seismic Data using Convolutional Neural Networks
Seismic data processing algorithms greatly benefit from regularly sampled and reliable data.
Facing Device Attribution Problem for Stabilized Video Sequences
Specifically, we propose: (i) a strategy to extract the characteristic fingerprint of a device, starting from either a set of images or stabilized video sequences; (ii) a strategy to match a stabilized video sequence with a given fingerprint in order to solve the device attribution problem.
Multimedia
Landmine Detection Using Autoencoders on Multi-polarization GPR Volumetric Data
This method works in an anomaly detection framework, indeed we only train the autoencoder on GPR data acquired on landmine-free areas.
A Counter-Forensic Method for CNN-Based Camera Model Identification
We examine in this paper the problem of identifying the camera model or type that was used to take an image and that can be spoofed.
Reliability Map Estimation For CNN-Based Camera Model Attribution
This refers to the problem of detecting which camera model has been used to acquire an image by only exploiting pixel information.
Satellite Image Forgery Detection and Localization Using GAN and One-Class Classifier
Specifically, we consider the scenario in which pixels within a region of a satellite image are replaced to add or remove an object from the scene.
Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization
As image tampering becomes ever more sophisticated and commonplace, the need for image forensics algorithms that can accurately and quickly detect forgeries grows.
First Steps Toward Camera Model Identification with Convolutional Neural Networks
Detecting the camera model used to shoot a picture enables to solve a wide series of forensic problems, from copyright infringement to ownership attribution.
