Luisa Verdoliva

Scientific Report on TUM-IAS Fellowship 

We in the Visual Computing Focus Group are research enthusiasts pushing the state of the art at the intersection of computer vision, graphics, and machine learning. Our research mission is to obtain high-quality digital models of the real world, which include detailed geometry, surface texture, and material in both static and dynamic environments. full report

Short CV

Luisa Verdoliva is Associate Professor at University Federico II of Naples (Italy). In 2018 she has been visiting professor at Friedrich-Alexander-University (FAU) in the Computer Graphics Group and in 2019-2020 she has been visiting scientist at Google AI in San Francisco in the Perception team. Her scientific interests are in the field of image processing, with main contributions in the area of multimedia forensics. She has been general co-Chair of the 2019 ACM Workshop on Information Hiding and Multimedia Security, technical Chair of the 2019 IEEE Workshop in Information Forensics and Security. Since 2016 she is area chair of IEEE ICIP. She is on the Editorial Board of IEEE Transactions on Information Forensics and Security and IEEE Signal Processing Letters. Dr. Verdoliva is Chair of the IEEE Signal Processing Society's Information Forensics and Security Technical Committee and has been elevated to the grade of IEEE Fellow, effective January 1, 2021. Her research is funded by DARPA, Google, Italian Ministry of Research.


Selected Awards

  • 2019, Best Paper Award to “Extracting camera-based fingerprints for video forensics”, IEEE CVPR Workshop on Media Forensics – Prize: GPU NVIDIA TITAN V.
  • 2018, Google Faculty Research Award (in Machine Perception): US$ 40.000.
  • 2018, Winner of the IEEE Signal Processing Cup - Prize: US$ 5.000.
  • 2018, IEEE Forensic Camera Model Identification Challenge – 3rd place (out of 582) on Kaggle - Prize: US$ 5.000.
  • 2017, Special Mention at Best Paper Awards to “PRNU-based forgery localization in a blind scenario”, International Conference on Image Analysis and Processing (ICIAP).
  • 2013, Winner of the IEEE Image Forensics Challenge - phase 2 (forgery localization) - Prize: US$ 1.750.
  • 2013, Winner of the IEEE Image Forensics Challenge - phase 1 (forgery detection) - Prize: US$ 1.500.

Research Interests

Image and video forgery detection and localization; deepfake video detection; GAN fingerprints attribution; source identification and blind clustering; biometrics liveness detection; image denoising and classification for remote sensing applications.


Selected Publications

Full list of publications: scholar.google.com/citations

1)     L. Verdoliva, “Media Forensics and DeepFakes: an overview”, IEEE Journal of Selected Topics in Signal Processing, in press, 2020.

2)     D. Cozzolino, L. Verdoliva, “Noiseprint: A CNN-based camera model fingerprint”, IEEE Transactions on Information Forensics and Security, vol. 15, no. 1, pp. 144-159, Jan. 2020.

3)     Rössler, D. Cozzolino, L. Verdoliva, C. Riess, J. Thies, M. Nießner: “FaceForensics++: Learning to Detect Manipulated Facial Images”, International Conference on Computer Vision, Seoul (Korea), Oct. 2019.

4)     D. Cozzolino, G. Poggi, L. Verdoliva, “Extracting camera-based fingerprints for video forensics” CVPR Workshop on Applications of Computer Vision and Pattern Recognition to Media Forensics, Long Beach (USA), June 2019.

5)     F. Marra, D. Gragnaniello, L. Verdoliva, G. Poggi, “Do GANs leave artificial fingerprints?” 2nd IEEE International Workshop on "Fake MultiMedia", San Jose (USA), March 2019.

6)     L. D’Amiano, D. Cozzolino, G. Poggi, L. Verdoliva, “A PatchMatch-based dense-field algorithm for video copy-move detection and localization”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 3, pp. 669-682, March 2019.

7)     F. Marra, G. Poggi, C. Sansone, L. Verdoliva: “Blind PRNU-based image clustering for source identification”, IEEE Transactions on Information Forensics and Security, vol. 12, no. 9, pp. 2197-2211, Sep. 2017.

8)     D. Cozzolino, G. Poggi, L. Verdoliva: “Recasting Residual-based Local Descriptors as Convolutional Neural Networks: An Application to Image Forgery Detection”, ACM Workshop on Information Hiding and Multimedia Security, Philadelphia (USA), June 2017.

9)     D. D'Avino, D. Cozzolino, G. Poggi, L. Verdoliva: “Autoencoder with Recurrent Neural Networks for video forgery detection”, IS&T Electronic Imaging: Media Watermarking, Security, and Forensics, Burlingame (USA), Jan. 2017.

10)  G. Chierchia, G. Poggi, C. Sansone, L. Verdoliva: “A Bayesian-MRF approach for PRNU-based image forgery detection”, IEEE Transactions on Information Forensics and Security, vol.9, pp.554-567, April 2014.


Publications as TUM-IAS Fellow

2022

  • Cozzolino, Davide; Nießner, Matthias; Verdoliva, Luisa: Audio-Visual Person-of-Interest DeepFake Detection. , 2022 more…
  • Sevastopolsky, Artem; Malkov, Yury; Durasov, Nikita; Verdoliva, Luisa; Nießner, Matthias: How to Boost Face Recognition with StyleGAN? , 2022 more…

2021

  • Cozzolino, Davide; Rössler, Andreas; Thies, Justus; Nießner, Matthias; Verdoliva, Luisa: ID-Reveal: Identity-aware DeepFake Video Detection. 2021 more…
  • Cozzolino, Davide; Thies, Justus; Rössler, Andreas; Nießner, Matthias; Verdoliva, Luisa: SpoC: Spoofing Camera Fingerprints. 2021 more…

2020

  • Cozzolino, Davide; Rössler, Andreas; Thies, Justus; Nießner, Matthias; Verdoliva, Luisa: ID-Reveal: Identity-aware DeepFake Video Detection. , 2020 more…

2019

  • Andreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, Matthias Nießner: FaceForensics++: Learning to Detect Manipulated Facial Images. 2019 more…
  • Cozzolino, Davide; Thies, Justus; Rössler, Andreas; Nießner, Matthias; Verdoliva, Luisa: SpoC: Spoofing Camera Fingerprints. , 2019 more…