no code implementations • 8 Apr 2024 • Antonio Giganti, Sara Mandelli, Paolo Bestagini, Umberto Giuriato, Alessandro D'Ausilio, Marco Marcon, Stefano Tubaro
Remarkably, we find that conditioning on future weather information has a greater impact than considering past traffic conditions.
no code implementations • 22 Feb 2024 • Amit Kumar Singh Yadav, Ziyue Xiang, Kratika Bhagtani, Paolo Bestagini, Stefano Tubaro, Edward J. Delp
We evaluate the detection performance of PS3DT on ASVspoof2019 dataset.
1 code implementation • 22 Jun 2023 • Antonio Giganti, Sara Mandelli, Paolo Bestagini, Marco Marcon, Stefano Tubaro
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.
no code implementations • 23 May 2023 • Antonio Giganti, Sara Mandelli, Paolo Bestagini, Marco Marcon, Stefano Tubaro
In this work, we propose a strategy to super-resolve coarse BVOC emission maps by simultaneously exploiting the contributions of different compounds.
no code implementations • 6 Apr 2023 • Amit Kumar Singh Yadav, Kratika Bhagtani, Ziyue Xiang, Paolo Bestagini, Stefano Tubaro, Edward J. Delp
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.
no code implementations • 15 Feb 2023 • Antonio Giganti, Sara Mandelli, Paolo Bestagini, Marco Marcon, Stefano Tubaro
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.
no code implementations • 31 Oct 2022 • Luigi Attorresi, Davide Salvi, Clara Borrelli, Paolo Bestagini, Stefano Tubaro
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.
1 code implementation • 20 Oct 2022 • Ziyue Xiang, Paolo Bestagini, Stefano Tubaro, Edward J. Delp
We denote our proposed technique as H. 264 Video Device Matching (H4VDM).
no code implementations • 19 Sep 2022 • Lydia Abady, Edoardo Daniele Cannas, Paolo Bestagini, Benedetta Tondi, Stefano Tubaro, Mauro Barni
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
no code implementations • 23 Jun 2022 • Antonio Giganti, Luca Cuccovillo, Paolo Bestagini, Patrick Aichroth, Stefano Tubaro
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.
no code implementations • 3 May 2022 • Emily R. Bartusiak, Sri Kalyan Yarlagadda, David Güera, Paolo Bestagini, Stefano Tubaro, Fengqing M. Zhu, Edward J. Delp
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.
1 code implementation • 4 Mar 2022 • Sara Mandelli, Nicolò Bonettini, Paolo Bestagini, Stefano Tubaro
For this reason, detecting if an image is an actual photograph or has been synthetically generated is becoming an urgent necessity.
no code implementations • 7 Jan 2022 • Edoardo Daniele Cannas, Nicolò Bonettini, Sara Mandelli, Paolo Bestagini, Stefano Tubaro
Synthetic Aperture Radar (SAR) images are a valuable asset for a wide variety of tasks.
no code implementations • 16 Dec 2021 • Sara Mandelli, Davide Cozzolino, Edoardo D. Cannas, Joao P. Cardenuto, Daniel Moreira, Paolo Bestagini, Walter J. Scheirer, Anderson Rocha, Luisa Verdoliva, Stefano Tubaro, Edward J. Delp
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.
no code implementations • 13 May 2021 • Ziyue Xiang, János Horváth, Sriram Baireddy, Paolo Bestagini, Stefano Tubaro, Edward J. Delp
Such manipulations can leave traces in the metadata embedded in video files.
no code implementations • 27 Jan 2021 • Francesco Picetti, Vincenzo Lipari, Paolo Bestagini, Stefano Tubaro
Data interpolation is a fundamental step in any seismic processing workflow.
1 code implementation • 7 Dec 2020 • Francesco Picetti, Sara Mandelli, Paolo Bestagini, Vincenzo Lipari, Stefano Tubaro
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.
no code implementations • 16 Nov 2020 • Luca Bondi, Edoardo Daniele Cannas, Paolo Bestagini, Stefano Tubaro
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.
no code implementations • 25 Sep 2020 • Sara Mandelli, Nicolò Bonettini, Paolo Bestagini, Stefano Tubaro
In this work, we focus on the effect that JPEG has on CNN training considering different computer vision and forensic image classification problems.
no code implementations • 24 Aug 2020 • Sebastiano Verde, Paolo Bestagini, Simone Milani, Giancarlo Calvagno, Stefano Tubaro
Forgery operations on video contents are nowadays within the reach of anyone, thanks to the availability of powerful and user-friendly editing software.
1 code implementation • 20 May 2020 • Sara Mandelli, Fabrizio Argenti, Paolo Bestagini, Massimo Iuliani, Alessandro Piva, Stefano Tubaro
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.
1 code implementation • 16 Apr 2020 • Nicolò Bonettini, Paolo Bestagini, Simone Milani, Stefano Tubaro
The advent of Generative Adversarial Network (GAN) architectures has given anyone the ability of generating incredibly realistic synthetic imagery.
2 code implementations • 16 Apr 2020 • Nicolò Bonettini, Edoardo Daniele Cannas, Sara Mandelli, Luca Bondi, Paolo Bestagini, Stefano Tubaro
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)
1 code implementation • 31 Jan 2020 • Sara Mandelli, Davide Cozzolino, Paolo Bestagini, Luisa Verdoliva, Stefano Tubaro
Source identification is an important topic in image forensics, since it allows to trace back the origin of an image.
2 code implementations • 20 Jun 2019 • David Güera, Sriram Baireddy, Paolo Bestagini, Stefano Tubaro, Edward J. Delp
Manipulating video content is easier than ever.
no code implementations • 11 Apr 2019 • Pedro Ribeiro Mendes Júnior, Luca Bondi, Paolo Bestagini, Stefano Tubaro, Anderson Rocha
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.
no code implementations • 23 Jan 2019 • Sara Mandelli, Vincenzo Lipari, Paolo Bestagini, Stefano Tubaro
Seismic data processing algorithms greatly benefit from regularly sampled and reliable data.
1 code implementation • 5 Nov 2018 • Sara Mandelli, Paolo Bestagini, Luisa Verdoliva, Stefano Tubaro
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
1 code implementation • 2 Oct 2018 • Paolo Bestagini, Federico Lombardi, Maurizio Lualdi, Francesco Picetti, Stefano Tubaro
This method works in an anomaly detection framework, indeed we only train the autoencoder on GPR data acquired on landmine-free areas.
no code implementations • 6 May 2018 • David Güera, Yu Wang, Luca Bondi, Paolo Bestagini, Stefano Tubaro, Edward J. Delp
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.
no code implementations • 4 May 2018 • David Güera, Sri Kalyan Yarlagadda, Paolo Bestagini, Fengqing Zhu, Stefano Tubaro, Edward J. Delp
This refers to the problem of detecting which camera model has been used to acquire an image by only exploiting pixel information.
1 code implementation • 13 Feb 2018 • Sri Kalyan Yarlagadda, David Güera, Paolo Bestagini, Fengqing Maggie Zhu, Stefano Tubaro, Edward J. Delp
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.
no code implementations • 8 Sep 2016 • Denis Tome', Luca Bondi, Emanuele Plebani, Luca Baroffio, Danilo Pau, Stefano Tubaro
Accurate pedestrian detection has a primary role in automotive safety: for example, by issuing warnings to the driver or acting actively on car's brakes, it helps decreasing the probability of injuries and human fatalities.
1 code implementation • 3 Mar 2016 • Luca Bondi, Luca Baroffio, David Güera, Paolo Bestagini, Edward J. Delp, Stefano Tubaro
Detecting the camera model used to shoot a picture enables to solve a wide series of forensic problems, from copyright infringement to ownership attribution.
1 code implementation • 13 Oct 2015 • Denis Tomè, Federico Monti, Luca Baroffio, Luca Bondi, Marco Tagliasacchi, Stefano Tubaro
Pedestrian detection is a popular research topic due to its paramount importance for a number of applications, especially in the fields of automotive, surveillance and robotics.
no code implementations • 27 Feb 2015 • Luca Baroffio, Matteo Cesana, Alessandro Redondi, Marco Tagliasacchi, Stefano Tubaro
Traditionally, a Compress-Then-Analyze approach has been pursued, in which sensing nodes acquire and encode the pixel-level representation of the visual content, that is subsequently transmitted to a sink node in order to be processed.
no code implementations • 26 Feb 2015 • Luca Baroffio, Antonio Canclini, Matteo Cesana, Alessandro Redondi, Marco Tagliasacchi, Stefano Tubaro
In this paper we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding.