no code implementations • 13 Feb 2024 • Thomas Pöllabauer, Julius Kühn, Jiayi Li, Arjan Kuijper
Estimating the 3D shape of an object using a single image is a difficult problem.
no code implementations • 8 Feb 2024 • Thomas Pöllabauer, Jan Emrich, Volker Knauthe, Arjan Kuijper
Estimating the 6D pose of objects accurately, quickly, and robustly remains a difficult task.
no code implementations • 22 Nov 2023 • Anton Winter, Nicolas Jourdan, Tristan Wirth, Volker Knauthe, Arjan Kuijper
In safety-critical domains such as autonomous driving and medical diagnosis, the reliability of machine learning models is crucial.
no code implementations • 20 Nov 2023 • Biying Fu, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
In previous works, a mobile application was developed using an unmodified commercial off-the-shelf smartphone to recognize whole-body exercises.
no code implementations • 7 Nov 2023 • Marco Huber, Anh Thi Luu, Fadi Boutros, Arjan Kuijper, Naser Damer
In this work, we investigate how the diversity of synthetic face recognition datasets compares to authentic datasets, and how the distribution of the training data of the generative models affects the distribution of the synthetic data.
1 code implementation • 9 Aug 2023 • Fadi Boutros, Jonas Henry Grebe, Arjan Kuijper, Naser Damer
The availability of large-scale authentic face databases has been crucial to the significant advances made in face recognition research over the past decade.
Ranked #2 on Synthetic Face Recognition on AgeDB-30 (Accuracy metric)
1 code implementation • 11 Jul 2023 • Fadi Boutros, Marcel Klemt, Meiling Fang, Arjan Kuijper, Naser Damer
To generate multiple samples of a certain synthetic identity, previous works proposed to disentangle the latent space of GANs by incorporating additional supervision or regularization, enabling the manipulation of certain attributes.
1 code implementation • 30 Apr 2023 • Jan Niklas Kolf, Tim Rieber, Jurek Elliesen, Fadi Boutros, Arjan Kuijper, Naser Damer
We empirically proved that our IDnet synthetic images are of higher identity discrimination in comparison to the conventional two-player GAN, while maintaining a realistic intra-identity variation.
no code implementations • 10 Apr 2023 • Igor Cherepanov, Jonathan Geraldi Joewono, Arjan Kuijper, Jörn Kohlhammer
This work presents an approach to detect frequent patterns in textual data that can be simultaneously registered during the file compression process with low consumption of resources.
1 code implementation • ICCV 2023 • Fadi Boutros, Jonas Henry Grebe, Arjan Kuijper, Naser Damer
The availability of large-scale authentic face databases has been crucial to the significant advances made in face recognition research over the past decade.
1 code implementation • 14 Nov 2022 • Fadi Boutros, Marcel Klemt, Meiling Fang, Arjan Kuijper, Naser Damer
In this paper, we propose an unsupervised face recognition model based on unlabeled synthetic data (USynthFace).
Ranked #1 on Unsupervised face recognition on LFW
no code implementations • 19 Oct 2022 • Marco Huber, Philipp Terhörst, Florian Kirchbuchner, Naser Damer, Arjan Kuijper
The confidence of a decision is often based on the overall performance of the model or on the image quality.
1 code implementation • 19 Sep 2022 • Meiling Fang, Wufei Yang, Arjan Kuijper, Vitomir Struc, Naser Damer
Face recognition (FR) algorithms have been proven to exhibit discriminatory behaviors against certain demographic and non-demographic groups, raising ethical and legal concerns regarding their deployment in real-world scenarios.
1 code implementation • 21 Jun 2022 • Fadi Boutros, Naser Damer, Arjan Kuijper
Deep learning-based face recognition models follow the common trend in deep neural networks by utilizing full-precision floating-point networks with high computational costs.
Ranked #1 on Quantization on LFW
no code implementations • 23 Mar 2022 • Philipp Terhörst, Florian Bierbaum, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
However, previous works followed evaluation settings consisting of older recognition models, limited cross-dataset and cross-model evaluations, and the use of low-scale testing data.
1 code implementation • 26 Nov 2021 • Philipp Terhörst, Malte Ihlefeld, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
These variabilities can be measured in terms of face image quality which is defined over the utility of a sample for recognition.
Ranked #1 on Face Verification on IJB-B
no code implementations • 8 Nov 2021 • Meiling Fang, Fadi Boutros, Arjan Kuijper, Naser Damer
Our proposed method outperforms established PAD methods in the CRMA database by reducing the mentioned shortcomings when facing masked faces.
1 code implementation • 21 Oct 2021 • Philipp Terhörst, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
To achieve this, a model-specific quality value of the input image is estimated and used to build a sample-specific quality regression model.
3 code implementations • 20 Sep 2021 • Fadi Boutros, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
The recent state-of-the-art face recognition solutions proposed to incorporate a fixed penalty margin on commonly used classification loss function, softmax loss, in the normalized hypersphere to increase the discriminative power of face recognition models, by minimizing the intra-class variation and maximizing the inter-class variation.
Ranked #1 on Face Recognition on IJB-B (TAR @ FAR=0.0001 metric)
1 code implementation • 16 Sep 2021 • Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
With the increased deployment of face recognition systems in our daily lives, face presentation attack detection (PAD) is attracting much attention and playing a key role in securing face recognition systems.
1 code implementation • 24 Aug 2021 • Fadi Boutros, Patrick Siebke, Marcel Klemt, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
However, this limits the deployment of such models that contain an extremely large number of parameters to embedded and low-end devices.
Ranked #2 on Lightweight Face Recognition on CALFW
no code implementations • 23 Aug 2021 • Naser Damer, Noemie Spiller, Meiling Fang, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
A face morphing attack image can be verified to multiple identities, making this attack a major vulnerability to processes based on identity verification, such as border checks.
no code implementations • 20 Aug 2021 • Naser Damer, Kiran Raja, Marius Süßmilch, Sushma Venkatesh, Fadi Boutros, Meiling Fang, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper
Face morphing attacks aim at creating face images that are verifiable to be the face of multiple identities, which can lead to building faulty identity links in operations like border checks.
1 code implementation • 27 Jul 2021 • Fadi Boutros, Naser Damer, Meiling Fang, Florian Kirchbuchner, Arjan Kuijper
In this paper, we present a set of extremely efficient and high throughput models for accurate face verification, MixFaceNets which are inspired by Mixed Depthwise Convolutional Kernels.
Ranked #3 on Lightweight Face Recognition on IJB-C
no code implementations • 29 Jun 2021 • Fadi Boutros, Naser Damer, Jan Niklas Kolf, Kiran Raja, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper, Pengcheng Fang, Chao Zhang, Fei Wang, David Montero, Naiara Aginako, Basilio Sierra, Marcos Nieto, Mustafa Ekrem Erakin, Ugur Demir, Hazim Kemal, Ekenel, Asaki Kataoka, Kohei Ichikawa, Shizuma Kubo, Jie Zhang, Mingjie He, Dan Han, Shiguang Shan, Klemen Grm, Vitomir Štruc, Sachith Seneviratne, Nuran Kasthuriarachchi, Sanka Rasnayaka, Pedro C. Neto, Ana F. Sequeira, Joao Ribeiro Pinto, Mohsen Saffari, Jaime S. Cardoso
These teams successfully submitted 18 valid solutions.
no code implementations • 28 Jun 2021 • Meiling Fang, Naser Damer, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
Iris presentation attack detection (PAD) plays a vital role in iris recognition systems.
1 code implementation • 10 Jun 2021 • Philipp Terhörst, André Boller, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
The implementation is publicly available.
no code implementations • 2 Mar 2021 • Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Face masks have become one of the main methods for reducing the transmission of COVID-19.
no code implementations • 2 Mar 2021 • Philipp Terhörst, Jan Niklas Kolf, Marco Huber, Florian Kirchbuchner, Naser Damer, Aythami Morales, Julian Fierrez, Arjan Kuijper
However, to enable a trustworthy FR technology, it is essential to know the influence of an extended range of facial attributes on FR beyond demographics.
1 code implementation • 2 Mar 2021 • Fadi Boutros, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Using the face as a biometric identity trait is motivated by the contactless nature of the capture process and the high accuracy of the recognition algorithms.
no code implementations • 2 Mar 2021 • Naser Damer, Fadi Boutros, Marius Süßmilch, Meiling Fang, Florian Kirchbuchner, Arjan Kuijper
This work provides a joint evaluation and in-depth analyses of the face verification performance of human experts in comparison to state-of-the-art automatic FR solutions.
no code implementations • 5 Dec 2020 • Adit Agarwal, Dr. K. K. Shukla, Arjan Kuijper, Anirban Mukhopadhyay
The ability to interpret decisions taken by Machine Learning (ML) models is fundamental to encourage trust and reliability in different practical applications.
1 code implementation • 2 Dec 2020 • Philipp Terhörst, Daniel Fährmann, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
In this work, we propose MAADFace, a new face annotations database that is characterized by the large number of its high-quality attribute annotations.
no code implementations • 28 Oct 2020 • Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
In this paper, we propose a lightweight framework to detect iris presentation attacks by extracting multiple micro-stripes of expanded normalized iris textures.
no code implementations • 20 Oct 2020 • Fadi Boutros, Naser Damer, Kiran Raja, Raghavendra Ramachandra, Florian Kirchbuchner, Arjan Kuijper
Motivated by the performance of iris recognition, we also propose the continuous authentication of users in a non-collaborative capture setting in HMD.
no code implementations • 21 Sep 2020 • Philipp Terhörst, Daniel Fährmann, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
For evaluating the predictability of the attributes, we trained a massive attribute classifier that is additionally able to accurately state its prediction confidence.
1 code implementation • 7 Sep 2020 • Min Cao, Chen Chen, Hao Dou, Xiyuan Hu, Silong Peng, Arjan Kuijper
Most existing person re-identification methods compute pairwise similarity by extracting robust visual features and learning the discriminative metric.
no code implementations • 1 Sep 2020 • Priyanka Das, Joseph McGrath, Zhaoyuan Fang, Aidan Boyd, Ganghee Jang, Amir Mohammadi, Sandip Purnapatra, David Yambay, Sébastien Marcel, Mateusz Trokielewicz, Piotr Maciejewicz, Kevin Bowyer, Adam Czajka, Stephanie Schuckers, Juan Tapia, Sebastian Gonzalez, Meiling Fang, Naser Damer, Fadi Boutros, Arjan Kuijper, Renu Sharma, Cunjian Chen, Arun Ross
Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection (PAD).
no code implementations • 27 Jul 2020 • Naser Damer, Jonas Henry Grebe, Cong Chen, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
The recent COVID-19 pandemic have increased the value of hygienic and contactless identity verification.
1 code implementation • 26 Jun 2020 • David Kügler, Marc Uecker, Arjan Kuijper, Anirban Mukhopadhyay
Despite recent successes, the advances in Deep Learning have not yet been fully translated to Computer Assisted Intervention (CAI) problems such as pose estimation of surgical instruments.
no code implementations • 28 Apr 2020 • Pavel Rojtberg, Thomas Pöllabauer, Arjan Kuijper
Given the dependency of current CNN architectures on a large training set, the possibility of using synthetic data is alluring as it allows generating a virtually infinite amount of labeled training data.
1 code implementation • 2 Apr 2020 • Philipp Terhörst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Face quality assessment aims at estimating the utility of a face image for the purpose of recognition.
3 code implementations • 20 Mar 2020 • Philipp Terhörst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Face image quality is an important factor to enable high performance face recognition systems.
Ranked #1 on Face Quality Assessement on LFW
no code implementations • 6 Mar 2020 • Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
With the widespread use of biometric systems, the demographic bias problem raises more attention.
1 code implementation • 21 Feb 2020 • Philipp Terhörst, Marco Huber, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Current research on soft-biometrics showed that privacy-sensitive information can be deduced from biometric templates of an individual.
1 code implementation • 10 Feb 2020 • Philipp Terhörst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
In contrast to previous works, our fair normalization approach enhances the overall performance by up to 53. 2% at false match rate of 0. 001 and up to 82. 9% at a false match rate of 0. 00001.
no code implementations • 13 Dec 2019 • Pavel Rojtberg, Arjan Kuijper
For objected detection, the availability of color cues strongly influences detection rates and is even a prerequisite for many methods.
no code implementations • 21 Oct 2019 • Naser Damer, Fadi Boutros, Khawla Mallat, Florian Kirchbuchner, Jean-Luc Dugelay, Arjan Kuijper
Generating visible-like face images from thermal images is essential to perform manual and automatic cross-spectrum face recognition.
1 code implementation • 9 Jul 2019 • Pavel Rojtberg, Arjan Kuijper
This work presents a pose selection method that finds a compact and robust set of calibration poses and is suitable for interactive calibration.
no code implementations • 25 Nov 2018 • Dongdong Zeng, Xiang Chen, Ming Zhu, Michael Goesele, Arjan Kuijper
Our proposed framework consists of two components, a traditional BGS segmenter $\mathcal{B}$ and a real-time semantic segmenter $\mathcal{S}$.
no code implementations • 13 Sep 2018 • Salome Kazeminia, Christoph Baur, Arjan Kuijper, Bram van Ginneken, Nassir Navab, Shadi Albarqouni, Anirban Mukhopadhyay
Generative Adversarial Networks (GANs) and their extensions have carved open many exciting ways to tackle well known and challenging medical image analysis problems such as medical image de-noising, reconstruction, segmentation, data simulation, detection or classification.
no code implementations • 5 Jul 2018 • Dongdong Zeng, Ming Zhu, Arjan Kuijper
Accurate and fast extraction of foreground object is a key prerequisite for a wide range of computer vision applications such as object tracking and recognition.
no code implementations • 25 Jun 2018 • David Kügler, Alexander Distergoft, Arjan Kuijper, Anirban Mukhopadhyay
Failure cases of black-box deep learning, e. g. adversarial examples, might have severe consequences in healthcare.
no code implementations • 19 Jun 2017 • Wei Zhou, Caiwen Ma, Arjan Kuijper
Especially in cluttered scenes there are many feature mismatches between scenes and models.
no code implementations • 14 Feb 2017 • Shan Gao, Xiaogang Chen, Qixiang Ye, Junliang Xing, Arjan Kuijper, Xiangyang Ji
Inspired with the social affinity property of moving objects, we propose a Graphical Social Topology (GST) model, which estimates the group dynamics by jointly modeling the group structure and the states of objects using a topological representation.