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检索条件"机构=Institute of Computer Science II-Computer Graphics"
2460 条 记 录,以下是51-60 订阅
排序:
AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge Distillation
arXiv
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arXiv 2024年
作者: Babnik, Žiga Boutros, Fadi Damer, Naser Peer, Peter Štruc, Vitomir University of Ljubljana Ljubljana Slovenia Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
Face Image Quality Assessment (FIQA) techniques have seen steady improvements over recent years, but their performance still deteriorates if the input face samples are not properly aligned. This alignment sensitivity ... 详细信息
来源: 评论
AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge Distillation
AI-KD: Towards Alignment Invariant Face Image Quality Assess...
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International Workshop on Biometrics and Forensics (IWBF)
作者: Žiga Babnik Fadi Boutros Naser Damer Peter Peer Vitomir Štrue University of Ljubljana Ljubljana Slovenia Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
Face Image Quality Assessment (FIQA) techniques have seen steady improvements over recent years, but their performance still deteriorates if the input face samples are not properly aligned. This alignment sensitivity ...
来源: 评论
ExFaceGAN: Exploring Identity Directions in GAN’s Learned Latent Space for Synthetic Identity Generation
ExFaceGAN: Exploring Identity Directions in GAN’s Learned L...
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IEEE International Joint Conference on Biometrics (IJCB)
作者: Fadi Boutros Marcel Klemt Meiling Fang Arjan Kuijper Naser Damer Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
Deep generative models have recently presented impressive results in generating realistic face images of random synthetic identities. To generate multiple samples of a certain synthetic identity, previous works propos...
来源: 评论
Bias and Diversity in Synthetic-based Face Recognition
arXiv
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arXiv 2023年
作者: Huber, Marco Luu, Anh Thi Boutros, Fadi Kuijper, Arjan Damer, Naser Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
Synthetic data is emerging as a substitute for authentic data to solve ethical and legal challenges in handling authentic face data. The current models can create real-looking face images of people who do not exist. H... 详细信息
来源: 评论
Are Explainability Tools Gender Biased? A Case Study on Face Presentation Attack Detection
arXiv
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arXiv 2023年
作者: Huber, Marco Fang, Meiling Boutros, Fadi Damer, Naser Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
Face recognition (FR) systems continue to spread in our daily lives with an increasing demand for higher explainability and interpretability of FR systems that are mainly based on deep learning. While bias across demo... 详细信息
来源: 评论
Weighting Attributes Based on the Greedy Algorithm Properties
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Procedia computer science 2024年 246卷 4883-4892页
作者: Beata Zielosko Urszula Stańczyk Kamil Jabloński University of Silesia in Katowice Institute of Computer Science Bȩdzińska 39 41-200 Sosnowiec Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A 44-100 Gliwice Poland
Estimation of importance for considered features is an important issue for any knowledge exploration process and it can be executed by a variety of approaches. In the research reported in this study, the primary aim w... 详细信息
来源: 评论
On the Quality and Diversity of Synthetic Face Data and its Relation to the Generator Training Data
On the Quality and Diversity of Synthetic Face Data and its ...
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International Workshop on Biometrics and Forensics (IWBF)
作者: Biying Fu Marcel Klemt Fadi Boutros Naser Damer Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
In recent years, advances in deep learning techniques and large-scale identity-labeled datasets have enabled facial recognition algorithms to rapidly gain performance. However, due to privacy issues, ethical concerns,...
来源: 评论
MorDIFF: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Diffusion Autoencoders
MorDIFF: Recognition Vulnerability and Attack Detectability ...
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International Workshop on Biometrics and Forensics (IWBF)
作者: Naser Damer Meiling Fang Patrick Siebke Jan Niklas Kolf Marco Huber Fadi Boutros Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
Investigating new methods of creating face morphing attacks is essential to foresee novel attacks and help mitigate them. Creating morphing attacks is commonly either performed on the image-level or on the representat...
来源: 评论
How Colorful Should Faces Be? Harmonizing Color and Model Quantization for Resource-restricted Face Recognition
How Colorful Should Faces Be? Harmonizing Color and Model Qu...
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IEEE International Joint Conference on Biometrics (IJCB)
作者: Jan Niklas Kolf Jurek Elliesen Fadi Boutros Naser Damer Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
State-of-the-art face recognition (FR) systems are based on overparameterized deep neural networks (DNN) which commonly use face images with 256 3 colors. The use of DNN and the storage of face images as references f...
来源: 评论
SynthASpoof: Developing Face Presentation Attack Detection Based on Privacy-friendly Synthetic Data
SynthASpoof: Developing Face Presentation Attack Detection B...
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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)
作者: Meiling Fang Marco Huber Naser Damer Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany
Recently, significant progress has been made in face presentation attack detection (PAD), which aims to secure face recognition systems against presentation attacks, owing to the availability of several face PAD datas...
来源: 评论