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Found 29 papers, 8 papers with code
NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.
E2F-Net: Eyes-to-Face Inpainting via StyleGAN Latent Space
We further improve the StyleGAN output to find the optimal code in the latent space using a new optimization for GAN inversion technique.
Robust Sclera Segmentation for Skin-tone Agnostic Face Image Quality Assessment
Face image quality assessment (FIQA) is crucial for obtaining good face recognition performance.
Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
We test the effectiveness of our approach by evaluating building segmentation performance on test datasets with varying label fractions.
Towards minimizing efforts for Morphing Attacks -- Deep embeddings for morphing pair selection and improved Morphing Attack Detection
The results endorse the advantages of face embeddings in more effective image pre-selection for face morphing and accurate detection of morphed face images.
Differential Newborn Face Morphing Attack Detection using Wavelet Scatter Network
Face Recognition System (FRS) are shown to be vulnerable to morphed images of newborns.
A Latent Fingerprint in the Wild Database
Further, existing databases for latent fingerprint recognition do not have a large number of unique subjects/fingerprint instances or do not provide ground truth/reference fingerprint images to conduct a cross-comparison against the latent.
Learning Pairwise Interaction for Generalizable DeepFake Detection
We obtain 98. 48% BOSC accuracy on the FF++ dataset and 90. 87% BOSC accuracy on the CelebDF dataset suggesting a promising direction for generalization of DeepFake detection.
SRTGAN: Triplet Loss based Generative Adversarial Network for Real-World Super-Resolution
We introduce a new triplet-based adversarial loss function that exploits the information provided in the LR image by using it as a negative sample.
Time flies by: Analyzing the Impact of Face Ageing on the Recognition Performance with Synthetic Data
The vast progress in synthetic image synthesis enables the generation of facial images in high resolution and photorealism.
SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data
The competition attracted a total of 12 participating teams, both from academia and industry and present in 11 different countries.
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
In this work, we investigate factors causing biased detection in public Deepfake datasets by (a) creating large-scale demographic and non-demographic attribute annotations with 47 different attributes for five popular Deepfake datasets and (b) comprehensively analysing attributes resulting in AI-bias of three state-of-the-art Deepfake detection backbone models on these datasets.
On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations
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.
Analyzing Human Observer Ability in Morphing Attack Detection -- Where Do We Stand?
One prevalent misconception is that an examiner's or observer's capacity for facial morph detection depends on their subject expertise, experience, and familiarity with the issue and that no works have reported the specific results of observers who regularly verify identity (ID) documents for their jobs.
Generation of Non-Deterministic Synthetic Face Datasets Guided by Identity Priors
Mated samples are generated by manipulating latent vectors, and more precisely, we exploit Principal Component Analysis (PCA) to define semantically meaningful directions in the latent space and control the similarity between the original and the mated samples using a pre-trained face recognition system.
QMagFace: Simple and Accurate Quality-Aware Face Recognition
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
Algorithmic Fairness in Face Morphing Attack Detection
In this paper, we study and present a comprehensive analysis of algorithmic fairness of the existing Single image-based Morph Attack Detection (S-MAD) algorithms.
Pixel-Level Face Image Quality Assessment for Explainable Face Recognition
To achieve this, a model-specific quality value of the input image is estimated and used to build a sample-specific quality regression model.
ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation
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.
MFR 2021: Masked Face Recognition Competition
These teams successfully submitted 18 valid solutions.
Learned Smartphone ISP on Mobile NPUs with Deep Learning, Mobile AI 2021 Challenge: Report
As the quality of mobile cameras starts to play a crucial role in modern smartphones, more and more attention is now being paid to ISP algorithms used to improve various perceptual aspects of mobile photos.
On the Applicability of Synthetic Data for Face Recognition
Face verification has come into increasing focus in various applications including the European Entry/Exit System, which integrates face recognition mechanisms.
Face Morphing Attack Generation & Detection: A Comprehensive Survey
The vulnerability of Face Recognition System (FRS) to various kind of attacks (both direct and in-direct attacks) and face morphing attacks has received a great interest from the biometric community.
On Benchmarking Iris Recognition within a Head-mounted Display for AR/VR Application
Motivated by the performance of iris recognition, we also propose the continuous authentication of users in a non-collaborative capture setting in HMD.
MIPGAN -- Generating Strong and High Quality Morphing Attacks Using Identity Prior Driven GAN
Extensive experiments are carried out to assess the FRS's vulnerability against the proposed morphed face generation technique on three types of data such as digital images, re-digitized (printed and scanned) images, and compressed images after re-digitization from newly generated MIPGAN Face Morph Dataset.
Can GAN Generated Morphs Threaten Face Recognition Systems Equally as Landmark Based Morphs? -- Vulnerability and Detection
\textit{(i) Can GAN generated morphs threaten Face Recognition Systems (FRS) equally as Landmark based morphs?}
On the Influence of Ageing on Face Morph Attacks: Vulnerability and Detection
To this extent, we have introduced a new morphed face dataset with ageing derived from the publicly available MORPH II face dataset, which we refer to as MorphAge dataset.
Morphing Attack Detection -- Database, Evaluation Platform and Benchmarking
Further, we present a new online evaluation platform to test algorithms on sequestered data.
Smartphone Multi-modal Biometric Authentication: Database and Evaluation
One of the unique features of this dataset is that it is collected in four different geographic locations representing a diverse population and ethnicity.
