Workshop on Deepfakes and Presentation Attacks in Biometrics Call for Papers

WACV2020 Workshop on Deepfakes and Presentation Attacks in Biometrics

Biometric recognition systems are vulnerable to different types of
presentation attacks (PAs), where an adversary presents a fabricated
artifact or altered trait to biometric sensors. The intent is often to
obfuscate one's own identity, create a synthetic identity, or to
spoof another person's identity. Typically observed attacks
include, but are not limited to printed attack, replay attack, makeup
attack and 3D mask attack. In order to detect or deflect presentation
attacks on biometric systems, numerous Presentation Attack Detection
(PAD, aka, anti-spoofing schemes) have been developed in the
literature, including sensor-based (e.g., RGB, Depth and IR) and
image-based solutions.

With the advent of techniques such as convolutional neural networks
(CNNs) and generative adversarial networks (GANs), more sophisticated
presentation attacks such as Deepfakes have emerged. Hence, it is
imperative to develop effective countermeasures to address these
challenges as well. The field of biometric security has attracted
great attention in recent years and has heavily investigated in a
number of projects including Tabula Rasa (EU project), ODIN (IARPA
project) and DARPA MediFor SAVI underlining the need to solutions to
defend against these attack vectors.

This workshop in WACV-2020 is being organized to reflect on these
specific issues, the impact and countermeasures for biometric
systems. The goal of this workshop is to bring experts from computer
vision, pattern recognition and image processing fields to advance the
state-of-the-art PAD solutions and Deepfake detection solutions.

Papers are invited to report on following topics, but not limited to:

        Novel attack mechanisms
        Novel physical attacks on biometric systems (e.g.,mask attacks).
        Approaches on evaluating the human perception in detecting such attacks
        Algorithmic advancements in detecting attacks
        Detection and mitigation of adversarial attacks
        Presentation Attack Detection (e.g., Face, Fingerprint and Iris )
        Deepfake attacks on biometrics and detection methods.
        Digital Manipulation
        Generalizability of Presentation Attack Detection
        Explainable AI in Presentation Attack
        Multi-modal Presentation Attack Detection
        Novel Presentation Attacks
        Novel Sensor-based Solutions
        Datasets and Evaluations
        Social and Ethical Implications
        Image Forensics
        Forgery Detection

Submission Guidelines:

    Papers presented at WACV workshops will be published as part of
    the "WACV Workshop Proceedings" and should, therefore, follow the
    same guideline as the main conference. Workshop papers will be
    included in IEEE Xplore, but will be indexed separately from the
    main conference papers. Paper submission guidlines of WACV can be
    accessed through this link.

    For review, a complete paper should be submitted using the
    for_review format and the guidelines provided in the author
    kit. All reviews are double-blind, so please be careful not to
    include any identifying information including the authors'
    names or affiliations.

    Accepted papers will be allocated 8 pages in the
    proceedings. Please note that References/Bibliography at the end
    of the paper will NOT count toward the aforementioned page
    limit. That is, a paper can be up to 8 pages + the references.

    The submission template can be downloaded here.

    Please submit your papers under:

Important Dates

    Workshop: The workshop will take place on WACV 2020 - March 5, 2020
    Full Paper Submission: 15th December, 2019
    Acceptance Notice: 10th January, 2020
    Camera-Ready Paper: 1st February, 2020

Organizing Committee:

    Kiran Raja, NTNU, Norway
    Naser Damer, Fraunhofer IGD, Germany
    Cunjian Chen, Michigan State University, USA
    Antitza Dantcheva, Inria, France
    Adam Czajka, University of Notre Dame, USA
    Hu Han, Chinese Academy of Sciences (CAS), China
    Raghavendra Ramachandra, NTNU, Norway