Papers Face Image Quality
“Face Image Quality” 태그가 달린 논문 54편 · 필터 해제
Demographic Variability in Face Image Quality Measures
Face image quality assessment (FIQA) algorithms are being integrated into online identity management applications. These applications allow users to upload a face image as part of their document issuance process, where t…
Face Image QualityFace Image Quality AssessmentImage Quality AssessmentManagementEye Sclera for Fair Face Image Quality Assessment
Fair operational systems are crucial in gaining and maintaining society's trust in face recognition systems (FRS). FRS start with capturing an image and assessing its quality before using it further for enrollment or ver…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality AssessmentFaceOracle: Chat with a Face Image Oracle
A face image is a mandatory part of ID and travel documents. Obtaining high-quality face images when issuing such documents is crucial for both human examiners and automated face recognition systems. In several internati…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality AssessmentRadial Distortion in Face Images: Detection and Impact
Acquiring face images of sufficiently high quality is important for online ID and travel document issuance applications using face recognition systems (FRS). Low-quality, manipulated (intentionally or unintentionally), o…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality AssessmentDeep Learning-based Compression Detection for explainable Face Image Quality Assessment
The assessment of face image quality is crucial to ensure reliable face recognition. In order to provide data subjects and operators with explainable and actionable feedback regarding captured face images, relevant quali…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality Assessment+1Impact of Face Alignment on Face Image Quality
Face alignment is a crucial step in preparing face images for feature extraction in facial analysis tasks. For applications such as face recognition, facial expression recognition, and facial attribute classification, al…
AttributeFace AlignmentFace DetectionFace Image Quality+5SynMorph: Generating Synthetic Face Morphing Dataset with Mated Samples
Face morphing attack detection (MAD) algorithms have become essential to overcome the vulnerability of face recognition systems. To solve the lack of large-scale and public-available datasets due to privacy concerns and …
Face Image QualityFace Image Quality AssessmentFace Morphing Attack DetectionFace Recognition+1DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformer
Generic Face Image Quality Assessment (GFIQA) evaluates the perceptual quality of facial images, which is crucial in improving image restoration algorithms and selecting high-quality face images for downstream tasks. We …
Face Image QualityFace Image Quality AssessmentImage Quality AssessmentImage Restoration+1Towards Inclusive Face Recognition Through Synthetic Ethnicity Alteration
Numerous studies have shown that existing Face Recognition Systems (FRS), including commercial ones, often exhibit biases toward certain ethnicities due to under-represented data. In this work, we explore ethnicity alter…
DiversityFace Image QualityFace Image Quality AssessmentFace Recognition+4GraFIQs: Face Image Quality Assessment Using Gradient Magnitudes
Face Image Quality Assessment (FIQA) estimates the utility of face images for automated face recognition (FR) systems. We propose in this work a novel approach to assess the quality of face images based on inspecting the…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality AssessmentAI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge Distillation
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 com…
Face AlignmentFace Image QualityFace Image Quality AssessmentFace Recognition+2IG-FIQA: Improving Face Image Quality Assessment through Intra-class Variance Guidance robust to Inaccurate Pseudo-Labels
In the realm of face image quality assesment (FIQA), method based on sample relative classification have shown impressive performance. However, the quality scores used as pseudo-labels assigned from images of classes wit…
Data AugmentationFace Image QualityFace Image Quality AssessmentImage Quality AssessmenteDifFIQA: Towards Efficient Face Image Quality Assessment Based On Denoising Diffusion Probabilistic Models
State-of-the-art Face Recognition (FR) models perform well in constrained scenarios, but frequently fail in difficult real-world scenarios, when no quality guarantees can be made for face samples. For this reason, Face I…
DenoisingFace Image QualityFace Image Quality AssessmentFace Recognition+3Efficient Expression Neutrality Estimation with Application to Face Recognition Utility Prediction
The recognition performance of biometric systems strongly depends on the quality of the compared biometric samples. Motivated by the goal of establishing a common understanding of face image quality and enabling system i…
BenchmarkingFace Image QualityFace RecognitionDouble Trouble? Impact and Detection of Duplicates in Face Image Datasets
Various face image datasets intended for facial biometrics research were created via web-scraping, i.e. the collection of images publicly available on the internet. This work presents an approach to detect both exactly a…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality AssessmentCLIB-FIQA: Face Image Quality Assessment with Confidence Calibration
Face Image Quality Assessment (FIQA) is pivotal for guaranteeing the accuracy of face recognition in unconstrained environments. Recent progress in deep quality-fitting-based methods that train models to align with q…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality AssessmentRobust Sclera Segmentation for Skin-tone Agnostic Face Image Quality Assessment
Face image quality assessment (FIQA) is crucial for obtaining good face recognition performance. FIQA algorithms should be robust and insensitive to demographic factors. The eye sclera has a consistent whitish color in a…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality AssessmentFace Image Quality Enhancement Study for Face Recognition
Unconstrained face recognition is an active research area among computer vision and biometric researchers for many years now. Still the problem of face recognition in low quality photos has not been well-studied so far. …
Face Image QualityFace RecognitionImage EnhancementA Study on the Impact of Face Image Quality on Face Recognition in the Wild
Deep learning has received increasing interests in face recognition recently. Large quantities of deep learning methods have been proposed to handle various problems appeared in face recognition. Quite a lot deep methods…
Deep LearningFace Image QualityFace RecognitionFace VerificationOptimization-Based Improvement of Face Image Quality Assessment Techniques
Contemporary face recognition (FR) models achieve near-ideal recognition performance in constrained settings, yet do not fully translate the performance to unconstrained (realworld) scenarios. To help improve the perform…
Face Image QualityFace Image Quality AssessmentFace RecognitionImage Quality Assessment