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Nils Hoffmann

Also published under: N. Hoffmann

Publications

Citations

874

Publications by Year

20092016

Co-Authors:

Markus AndresenLucian AsiminoaeiJörg DannehlM. FischerF. W. Fuchs

Show All Co-Authors (21)

Nils Hoffmann

Also published under: N. Hoffmann

Affiliation

Department for Research and Product Development

Ingenieurbüro Hoffmann GmbH

Halle/Peißen, Germany

Publication Topics

Active Damping,
Current Control,
Point Of Common Coupling,
Discrete-time Domain,
Extended Kalman Filter,
Grid Conditions,
Grid Impedance,
Grid Voltage,
Kalman Filter,
LCL Filter,
Resonance Frequency,
State Feedback

Biography

Nils Hoffmann (S'09–M'14) was born in Halle/Saale, Germany, in 1983. He received the Dipl.-Ing. and Dr.-Ing. degrees from the Christian-Albrechts-University of Kiel, Kiel, Germany, in 2009 and 2014, respectively.,Between 2009 and 2013, he was with the Institute of Power Electronics and Electrical Drives, Christian-Albrechts-University of Kiel, working on modern control strategies applied to grid-connected power converter systems. Since 2013, he has been with the Ingenieurbüro Hoffmann GmbH in Halle/Saale, where he is the Head of research and product development for power electronics and electrical drives. His work involves modern and innovative concepts of power electronic systems, electrical drives and renewable energy applications w...

Publications

Citations

874

Publications by Year

20092016

Co-Authors:

Markus Andresen
Lucian Asiminoaei
Jörg Dannehl
M. Fischer
F. W. Fuchs

Show All Co-Authors (21)

Author's Published Works

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Showing 1-10 of 10 results

Conferences (8)

Journals (2)

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Christoph Busch(6)
Mathias Ibsen(6)
Christian Rathgeb(5)
C. Rathgeb(4)
C. Busch(4)
Biometrics Security and Privacy Group, Idiap Research Institute, Martigny, Switzerland(2)
da/sec-Biometrics and Security Research Group, Hochschule Darmstadt, Germany(1)
Biometrics and Internet Security Research Group, Hochschule Darmstadt, Darmstadt, Germany(1)
Biometrics and Security Research Group, Hochschule Darmstadt, Darmstadt, Germany(1)
Da/sec – Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany(1)
2021 IEEE International Workshop on Information Forensics and Security (WIFS)(1)
2022 IEEE International Conference on Image Processing (ICIP)(1)
2022 International Workshop on Biometrics and Forensics (IWBF)(1)
2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)(1)
2024 12th International Workshop on Biometrics and Forensics (IWBF)(1)
IEEE(10)
Bordeaux, France(1)
Enschede, Netherlands(1)
Istanbul, Turkiye(1)
Montpellier, France(1)
Rhodes Island, Greece(1)
Face Images(9)
Face Recognition(8)
Convolutional Neural Network(3)
Digital Manipulation(3)
Face Detection(3)

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SynChildFace: Fine-tuning Face Recognition for Children with Synthetic Data

Franck V. Souop Kouam;Christian Rathgeb;Mathias Ibsen;Christoph Busch

2024 IEEE International Workshop on Information Forensics and Security (WIFS)

Year: 2024 | Conference Paper |

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Many forensic investigations (e.g., the search for missing children or analysis of child pornographic data) require robust face recognition of children. However, face recognition systems are primarily designed for recognizing adults, and previous studies have already shown that they do not reliably recognize children. Moreover, the limited availability of public datasets and ethical as well as pri...Show More

SynChildFace: Fine-tuning Face Recognition for Children with Synthetic Data

Franck V. Souop Kouam;Christian Rathgeb;Mathias Ibsen;Christoph Busch

2024 IEEE International Workshop on Information Forensics and Security (WIFS)

Year: 2024 | Conference Paper |

Multi-Channel Cross Modal Detection of Synthetic Face Images

M. Ibsen;C. Rathgeb;S. Marcel;C. Busch

2024 12th International Workshop on Biometrics and Forensics (IWBF)

Year: 2024 | Conference Paper |

Cited by: Papers (1)

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Synthetically generated face images have shown to be indistinguishable from real images by humans and as such can lead to a lack of trust in digital content as they can, for instance, be used to spread misinformation. Therefore, the need to develop algorithms for detecting entirely synthetic face images is apparent. Of interest are images generated by state-of-the-art deep learning-based models, a...Show More

Multi-Channel Cross Modal Detection of Synthetic Face Images

M. Ibsen;C. Rathgeb;S. Marcel;C. Busch

2024 12th International Workshop on Biometrics and Forensics (IWBF)

Year: 2024 | Conference Paper |

TetraLoss: Improving the Robustness of Face Recognition Against Morphing Attacks

Mathias Ibsen;L. J. Gonzalez-Soler;Christian Rathgeb;Christoph Busch

2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG)

Year: 2024 | Conference Paper |

Cited by: Papers (3)

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Face recognition systems are widely deployed in high-security applications such as for biometric verification at border controls. Despite their high accuracy on pristine data, it is well-known that digital manipulations, such as face morphing, pose a security threat to face recognition systems. Malicious actors can exploit the facilities offered by the identity document issuance process to obtain ...Show More

TetraLoss: Improving the Robustness of Face Recognition Against Morphing Attacks

Mathias Ibsen;L. J. Gonzalez-Soler;Christian Rathgeb;Christoph Busch

2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG)

Year: 2024 | Conference Paper |

Attacking Face Recognition With T-Shirts: Database, Vulnerability Assessment, and Detection

Mathias Ibsen;Christian Rathgeb;Fabian Brechtel;Ruben Klepp;Katrin Pöppelmann;Anjith George;Sébastien Marcel;Christoph Busch

IEEE Access

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (5)

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Face recognition systems are widely deployed for biometric authentication. Despite this, it is well-known that, without any safeguards, face recognition systems are highly vulnerable to presentation attacks. In response to this security issue, several promising methods for detecting presentation attacks have been proposed which show high performance on existing benchmarks. However, an ongoing chal...Show More

Attacking Face Recognition With T-Shirts: Database, Vulnerability Assessment, and Detection

Mathias Ibsen;Christian Rathgeb;Fabian Brechtel;Ruben Klepp;Katrin Pöppelmann;Anjith George;Sébastien Marcel;Christoph Busch

IEEE Access

Year: 2023 | Volume: 11 | Journal Article |

Benchmarking Cross-Domain Face Recognition with Avatars, Caricatures and Sketches

A. Foroughi;C. Rathgeb;M. Ibsen;C. Busch

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2023 | Conference Paper |

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The accuracy of face recognition skyrocketed in past years and its robustness towards various covariates has been shown, such as variations in pose or age. In recent years, a considerable amount of research efforts has been devoted to cross-domain face recognition aiming at comparing facial images obtained from domains that are different in capture technologies, e.g. visible spectrum versus infrar...Show More

Benchmarking Cross-Domain Face Recognition with Avatars, Caricatures and Sketches

A. Foroughi;C. Rathgeb;M. Ibsen;C. Busch

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2023 | Conference Paper |

A Principal Component Analysis-Based Approach for Single Morphing Attack Detection

Laurine Dargaud;Mathias Ibsen;Juan Tapia;Christoph Busch

2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)

Year: 2023 | Conference Paper |

Cited by: Papers (6)

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This paper proposes an explicit method for single face image morphing attack detection, using an RGB decomposition based on Principal Component Analysis from texture patterns. Handcrafted detection algorithms can be advantageous over deep learning-based methods as they constitute increased explainability, showcased in this work by visualizing relevant face areas for morphing attack detection. Such...Show More

A Principal Component Analysis-Based Approach for Single Morphing Attack Detection

Laurine Dargaud;Mathias Ibsen;Juan Tapia;Christoph Busch

2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)

Year: 2023 | Conference Paper |

Fun Selfie Filters in Face Recognition: Impact Assessment and Removal

Cristian Botezatu;Mathias Ibsen;Christian Rathgeb;Christoph Busch

IEEE Transactions on Biometrics, Behavior, and Identity Science

Year: 2023 | Volume: 5, Issue: 1 | Journal Article |

Cited by: Papers (10)

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This work investigates the impact of fun selfie filters, which are frequently used to modify selfies, on face recognition systems. Based on a qualitative assessment and classification of freely available mobile applications, ten relevant fun selfie filters are selected to create a database. To this end, the selected filters are automatically applied to face images of public face image databases. D...Show More

Fun Selfie Filters in Face Recognition: Impact Assessment and Removal

Cristian Botezatu;Mathias Ibsen;Christian Rathgeb;Christoph Busch

IEEE Transactions on Biometrics, Behavior, and Identity Science

Year: 2023 | Volume: 5, Issue: 1 | Journal Article |

Crowd-Powered Face Manipulation Detection: Fusing Human Examiner Decisions

C. Rathgeb;R. Nichols;M. Ibsen;P. Drozdowski;C. Busch

2022 IEEE International Conference on Image Processing (ICIP)

Year: 2022 | Conference Paper |

Cited by: Papers (5)

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We investigate the potential of fusing human examiner decisions for the task of digital face manipulation detection. To this end, various decision fusion methods are proposed incorporating the examiners’ decision confidence, experience level, and their time to take a decision. Conducted experiments are based on a psychophysical evaluation of digital face image manipulation detection capabilities o...Show More

Crowd-Powered Face Manipulation Detection: Fusing Human Examiner Decisions

C. Rathgeb;R. Nichols;M. Ibsen;P. Drozdowski;C. Busch

2022 IEEE International Conference on Image Processing (ICIP)

Year: 2022 | Conference Paper |

Are average Faces Master Faces?

André Dörsch;Christian Rathgeb;Mathias Ibsen;Christoph Busch

2022 International Workshop on Biometrics and Forensics (IWBF)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

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So-called master faces are faces for which the probability of achieving a false match when being compared against an unknown set of face images is significantly higher than that of a random impostor. In this work, we investigate whether average faces exhibit said property of master faces. In order to generate average faces for different demographic groups, face morphing is applied to images of pub...Show More

Are average Faces Master Faces?

André Dörsch;Christian Rathgeb;Mathias Ibsen;Christoph Busch

2022 International Workshop on Biometrics and Forensics (IWBF)

Year: 2022 | Conference Paper |

Differential Anomaly Detection for Facial Images

M. Ibsen;L. J. Gonzalez-Soler;C. Rathgeb;P. Drozdowski;M. Gomez-Barrero;C. Busch

2021 IEEE International Workshop on Information Forensics and Security (WIFS)

Year: 2021 | Conference Paper |

Cited by: Papers (9)

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Due to their convenience and high accuracy, face recognition systems are widely employed in governmental and personal security applications to automatically recognise individuals. Despite recent advances, face recognition systems have shown to be particularly vulnerable to identity attacks (i.e., digital manipulations and attack presentations). Identity attacks pose a big security threat as they c...Show More

Differential Anomaly Detection for Facial Images

M. Ibsen;L. J. Gonzalez-Soler;C. Rathgeb;P. Drozdowski;M. Gomez-Barrero;C. Busch

2021 IEEE International Workshop on Information Forensics and Security (WIFS)

Year: 2021 | Conference Paper |

Author details

Nils Hoffmann

Nils Hoffmann

Affiliation

Publication Topics

Biography

Showing 1-10 of 10 results

Show

SynChildFace: Fine-tuning Face Recognition for Children with Synthetic Data

SynChildFace: Fine-tuning Face Recognition for Children with Synthetic Data

Multi-Channel Cross Modal Detection of Synthetic Face Images

Multi-Channel Cross Modal Detection of Synthetic Face Images

TetraLoss: Improving the Robustness of Face Recognition Against Morphing Attacks

TetraLoss: Improving the Robustness of Face Recognition Against Morphing Attacks

Attacking Face Recognition With T-Shirts: Database, Vulnerability Assessment, and Detection

Attacking Face Recognition With T-Shirts: Database, Vulnerability Assessment, and Detection

Benchmarking Cross-Domain Face Recognition with Avatars, Caricatures and Sketches

Benchmarking Cross-Domain Face Recognition with Avatars, Caricatures and Sketches

A Principal Component Analysis-Based Approach for Single Morphing Attack Detection

A Principal Component Analysis-Based Approach for Single Morphing Attack Detection

Fun Selfie Filters in Face Recognition: Impact Assessment and Removal

Fun Selfie Filters in Face Recognition: Impact Assessment and Removal

Crowd-Powered Face Manipulation Detection: Fusing Human Examiner Decisions

Crowd-Powered Face Manipulation Detection: Fusing Human Examiner Decisions

Are average Faces Master Faces?

Are average Faces Master Faces?

Differential Anomaly Detection for Facial Images

Differential Anomaly Detection for Facial Images

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