LivDet 2013 Fingerprint Liveness Detection Competition 2013
By Luca Ghiani, David Yambay, Valerio Mura, Simona Tocco, Gian Luca Marcialis, Fabio Roli, Stephanie A. C. Schuckers. 2013
202 citations recorded by the source corpus.
Subfields: Information Systems, Safety Research, Signal Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Fabio Roli
- Sébastien Marcel
- Gian Luca Marcialis
- Julian Fierrez
- James M. Ferryman
- Peter Wild
- Lulu Chen
- Petru Radu
In Safety Research
- James M. Ferryman
- Peter Wild
- Lulu Chen
- Petru Radu
- Fabio Roli
- Luca Ghiani
- Gian Luca Marcialis
- Sébastien Marcel
In Signal Processing
- Fabio Roli
- Julian Fierrez
- Sébastien Marcel
- Gian Luca Marcialis
- Javier Galbally
- James M. Ferryman
- Peter Wild
- Lulu Chen
Citations in the corpus
- Biometric Antispoofing Methods: A Survey in Face Recognition (2014, methodology): “In most cases, these datasets have been generated in the framework of international evaluation competitions such as the series of Fingerprint Liveness Detection Competitions, LivDet, held biennially since 2009 [55], [169], [170], or themore recent 2DFaceAnti-Spoofing contests that started in 2011 [5”
- Semi-supervised stacked autoencoder-based deep hierarchical semantic feature for real-time fingerprint liveness detection (2019, methodology): “…which are RFLD with semi-supervised stacked autoencoder and RFLD without semi-supervised stacked autoencoder, have been evaluated on two public fingerprint datasets: LivDet 2011 [1] and 2013 [25], and they were released, respectively, from 2011 and 2013 Fingerprint Liveness Detection Competition.”
- LivDet 2015 fingerprint liveness detection competition 2015 (2015, background): “The second and third editions of Liveness Detection Competition (LivDet 2011 [8], LivDet 2013 [1]) included integrated system testing.”
- Fingerprint Liveness Detection Using Convolutional Neural Networks (2016, methodology): “The datasets provided by the Liveness Detection Competition (LivDet) in the years of 2009 [39], 2011 [40], and 2013 [41] are used in this study.”
- Towards anomaly detection for increased security in multibiometric systems: Spoofing-resistant 1-median fusion eliminating outliers (2014, methodology): “In order to address the spoofing issue, liveness detection methods [4, 5] have been proposed using additional data to assess if the biometric is authentic.”