1 code implementation • 5 May 2022 • Eklavya Sarkar, Pavel Korshunov, Laurent Colbois, Sébastien Marcel
Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered.
1 code implementation • 9 Dec 2020 • Eklavya Sarkar, Pavel Korshunov, Laurent Colbois, Sébastien Marcel
Morphing attacks is a threat to biometric systems where the biometric reference in an identity document can be altered.
no code implementations • 7 Sep 2020 • Pavel Korshunov, Sébastien Marcel
In response to the threat such manipulations can pose to our trust in video evidence, several large datasets of deepfake videos and many methods to detect them were proposed recently.
no code implementations • 6 Nov 2019 • Md Sahidullah, Jose Patino, Samuele Cornell, Ruiqing Yin, Sunit Sivasankaran, Hervé Bredin, Pavel Korshunov, Alessio Brutti, Romain Serizel, Emmanuel Vincent, Nicholas Evans, Sébastien Marcel, Stefano Squartini, Claude Barras
This paper describes the speaker diarization systems developed for the Second DIHARD Speech Diarization Challenge (DIHARD II) by the Speed team.
3 code implementations • 4 Nov 2019 • Hervé Bredin, Ruiqing Yin, Juan Manuel Coria, Gregory Gelly, Pavel Korshunov, Marvin Lavechin, Diego Fustes, Hadrien Titeux, Wassim Bouaziz, Marie-Philippe Gill
We introduce pyannote. audio, an open-source toolkit written in Python for speaker diarization.
Ranked #1 on Speaker Diarization on ETAPE
no code implementations • 3 Oct 2019 • Pavel Korshunov, Sébastien Marcel
We show that the state of the art face recognition systems based on VGG and Facenet neural networks are vulnerable to the deep morph videos, with 85. 62 and 95. 00 false acceptance rates, respectively, which means methods for detecting these videos are necessary.
1 code implementation • 20 Dec 2018 • Pavel Korshunov, Sebastien Marcel
The best performing method, which is based on visual quality metrics and is often used in presentation attack detection domain, resulted in 8. 97% equal error rate on high quality Deepfakes.