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Found 16 papers, 1 papers with code
Exploring 3D Face Reconstruction and Fusion Methods for Face Verification: A Case-Study in Video Surveillance
3D face reconstruction (3DFR) algorithms are based on specific assumptions tailored to distinct application scenarios.
SDFR: Synthetic Data for Face Recognition Competition
The submitted models were trained on existing and also new synthetic datasets and used clever methods to improve training with synthetic data.
LivDet2023 -- Fingerprint Liveness Detection Competition: Advancing Generalization
The International Fingerprint Liveness Detection Competition (LivDet) is a biennial event that invites academic and industry participants to prove their advancements in Fingerprint Presentation Attack Detection (PAD).
3D Face Reconstruction: the Road to Forensics
Therefore, it provides an analysis of the achievements of 3D face reconstruction algorithms from surveillance videos and mugshot images and discusses the current obstacles that separate 3D face reconstruction from an active role in forensic applications.
3D Face Reconstruction for Forensic Recognition -- A Survey
3D face reconstruction algorithms from images and videos are applied to many fields, from plastic surgery to the entertainment sector, thanks to their advantageous features.
Review of the Fingerprint Liveness Detection (LivDet) competition series: from 2009 to 2021
Fingerprint authentication systems are highly vulnerable to artificial reproductions of fingerprint, called fingerprint presentation attacks.
Fingerprint recognition with embedded presentation attacks detection: are we ready?
Accordingly, this paper explores the fusion of PAD into verification systems by proposing a novel investigation instrument: a performance simulator based on the probabilistic modeling of the relationships among the Receiver Operating Characteristics (ROC) of the two individual systems when PAD and verification stages are implemented sequentially.
LivDet 2021 Fingerprint Liveness Detection Competition -- Into the unknown
The International Fingerprint Liveness Detection Competition is an international biennial competition open to academia and industry with the aim to assess and report advances in Fingerprint Presentation Attack Detection.
Electroencephalography signal processing based on textural features for monitoring the driver's state by a Brain-Computer Interface
The claim is that the class transitions can be detected by describing the variations of the micro-patterns' occurrences along the EEG signal.
Detecting Anomalies from Video-Sequences: a Novel Descriptor
We present a novel descriptor for crowd behavior analysis and anomaly detection.
Are Adaptive Face Recognition Systems still Necessary? Experiments on the APE Dataset
In the last five years, deep learning methods, in particular CNN, have attracted considerable attention in the field of face-based recognition, achieving impressive results.
Are spoofs from latent fingerprints a real threat for the best state-of-art liveness detectors?
We investigated the threat level of realistic attacks using latent fingerprints against sensors equipped with state-of-art liveness detectors and fingerprint verification systems which integrate such liveness algorithms.
A novel classification-selection approach for the self updating of template-based face recognition systems
Consequently, computational complexity and storage space tend to be among the critical requirements of these algorithms.
Analysis of "User-Specific Effect" and Impact of Operator Skills on Fingerprint PAD Systems
Fingerprint Liveness detection, or presentation attacks detection (PAD), that is, the ability of detecting if a fingerprint submitted to an electronic capture device is authentic or made up of some artificial materials, boosted the attention of the scientific community and recently machine learning approaches based on deep networks opened novel scenarios.
LivDet in Action - Fingerprint Liveness Detection Competition 2019
The International Fingerprint liveness Detection Competition (LivDet) is an open and well-acknowledged meeting point of academies and private companies that deal with the problem of distinguishing images coming from reproductions of fingerprints made of artificial materials and images relative to real fingerprints.
LivDet 2017 Fingerprint Liveness Detection Competition 2017
Fingerprint Presentation Attack Detection (FPAD) deals with distinguishing images coming from artificial replicas of the fingerprint characteristic, made up of materials like silicone, gelatine or latex, and images coming from alive fingerprints.
