LivDet 2021 Fingerprint Liveness Detection Competition -- Into the
unknown
- URL: http://arxiv.org/abs/2108.10183v1
- Date: Mon, 23 Aug 2021 13:53:25 GMT
- Title: LivDet 2021 Fingerprint Liveness Detection Competition -- Into the
unknown
- Authors: Roberto Casula, Marco Micheletto, Giulia Orr\`u, Rita Delussu, Sara
Concas, Andrea Panzino, Gian Luca Marcialis
- Abstract summary: The International Fingerprint Liveness Detection Competition is an international biennial competition open to academia and industry.
Twenty-three algorithms were submitted to the competition, the maximum number ever achieved by LivDet.
- Score: 1.75485410385325
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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. The
proposed "Liveness Detection in Action" and "Fingerprint representation"
challenges were aimed to evaluate the impact of a PAD embedded into a
verification system, and the effectiveness and compactness of feature sets for
mobile applications. Furthermore, we experimented a new spoof fabrication
method that has particularly affected the final results. Twenty-three
algorithms were submitted to the competition, the maximum number ever achieved
by LivDet.
Related papers
- SynFacePAD 2023: Competition on Face Presentation Attack Detection Based
on Privacy-aware Synthetic Training Data [51.42380508231581]
The paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJCB 2023)
The competition aimed to motivate and attract solutions that target detecting face presentation attacks while considering synthetic-based training data motivated by privacy, legal and ethical concerns associated with personal data.
The submitted solutions presented innovations and novel approaches that led to outperforming the considered baseline in the investigated benchmarks.
arXiv Detail & Related papers (2023-11-09T13:02:04Z) - Liveness Detection Competition -- Noncontact-based Fingerprint
Algorithms and Systems (LivDet-2023 Noncontact Fingerprint) [12.05273326660349]
LivDet-2023 Noncontact Fingerprint is the first edition of the noncontact fingerprint-based PAD competition for algorithms and systems.
The competition serves as an important benchmark in noncontact-based fingerprint PAD.
The winning algorithm achieved an APCER of 11.35% averaged overall PAIs and a BPCER of 0.62%.
arXiv Detail & Related papers (2023-10-01T12:59:30Z) - LivDet2023 -- Fingerprint Liveness Detection Competition: Advancing
Generalization [6.154783360142315]
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)
This edition, LivDet2023, proposed two challenges, Liveness Detection in Action and Fingerprint Representation, to evaluate the efficacy of PAD embedded in verification systems and the effectiveness and compactness of feature sets.
arXiv Detail & Related papers (2023-09-27T11:24:01Z) - The Robust Semantic Segmentation UNCV2023 Challenge Results [99.97867942388486]
This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023.
The challenge was centered around semantic segmentation in urban environments, with a particular focus on natural adversarial scenarios.
The report presents the results of 19 submitted entries, with numerous techniques drawing inspiration from cutting-edge uncertainty quantification methodologies.
arXiv Detail & Related papers (2023-09-27T08:20:03Z) - DyFFPAD: Dynamic Fusion of Convolutional and Handcrafted Features for Fingerprint Presentation Attack Detection [1.9573380763700712]
A presentation attack can be performed by creating a spoof of a user's fingerprint with or without their consent.
This paper presents a dynamic ensemble of deep CNN and handcrafted features to detect presentation attacks.
We have validated our proposed method on benchmark databases from the Liveness Detection Competition.
arXiv Detail & Related papers (2023-08-19T13:46:49Z) - EFaR 2023: Efficient Face Recognition Competition [51.77649060180531]
The paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023)
The competition received 17 submissions from 6 different teams.
The submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size.
arXiv Detail & Related papers (2023-08-08T09:58:22Z) - Review of the Fingerprint Liveness Detection (LivDet) competition
series: from 2009 to 2021 [3.0828074702828623]
The International Fingerprint liveness Detection Competition (LivDet) has been running biannually since 2009.
This paper reviews the LivDet editions from 2009 to 2021 and points out their evolution over the years.
arXiv Detail & Related papers (2022-02-15T09:14:08Z) - Review of Face Presentation Attack Detection Competitions [48.051950472633685]
Face presentation attack detection (PAD) has received increasing attention ever since the vulnerabilities to spoofing have been widely recognized.
The state of the art in unimodal and multi-modal face anti-spoofing has been assessed in eight international competitions.
arXiv Detail & Related papers (2021-12-21T15:20:10Z) - ASVspoof 2021: accelerating progress in spoofed and deepfake speech
detection [70.45884214674057]
ASVspoof 2021 is the forth edition in the series of bi-annual challenges which aim to promote the study of spoofing.
This paper describes all three tasks, the new databases for each of them, the evaluation metrics, four challenge baselines, the evaluation platform and a summary of challenge results.
arXiv Detail & Related papers (2021-09-01T16:17:31Z) - DeeperForensics Challenge 2020 on Real-World Face Forgery Detection:
Methods and Results [144.5252578415748]
This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection.
The challenge employs the DeeperForensics-1.0 dataset, with 60,000 videos constituted by a total of 17.6 million frames.
A total of 115 participants registered for the competition, and 25 teams made valid submissions.
arXiv Detail & Related papers (2021-02-18T16:48:57Z) - DeFraudNet:End2End Fingerprint Spoof Detection using Patch Level
Attention [11.978082858160572]
Cross sensor and cross material spoof detection still pose a challenge for fingerprint recognition systems.
This paper proposes a novel method for fingerprint spoof detection using both global and local fingerprint feature descriptors.
A novel patch attention network is used for finding the most discriminative patches and also for network fusion.
arXiv Detail & Related papers (2020-02-19T14:41:06Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.