Papers Face Image Quality Assessment
“Face Image Quality Assessment” 태그가 달린 논문 56편 · 필터 해제
Employing Vision-Language Models for Face Image Quality Assessment
Face Image Quality Assessment (FIQA) is a crucial control step in biometric pipelines. It ensures only reliable samples are processed to maintain system accuracy. State-of-the-art FIQA methods achieve high utility but ty…
Face Image Quality AssessmentPreFIQs: Face Image Quality Is What Survives Pruning
Face Image Quality Assessment (FIQA) evaluates the utility of a face image for automated face recognition (FR) systems. In this work, we propose PreFIQs, an unsupervised and training-free FIQA framework grounded in the P…
Face Image Quality AssessmentFace RecognitionFunFace: Feature Utility and Norm Estimation for Face Recognition
Face Recognition (FR) is used in a variety of application domains, from entertainment and banking to security and surveillance. Such applications rely on the FR model to be robust and perform well in a variety of setting…
Face Image Quality AssessmentFace RecognitionATTN-FIQA: Interpretable Attention-based Face Image Quality Assessment with Vision Transformers
Face Image Quality Assessment (FIQA) aims to assess the recognition utility of face samples and is essential for reliable face recognition (FR) systems. Existing approaches require computationally expensive procedures su…
Face Image Quality AssessmentFace RecognitionEX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment
Face Image Quality Assessment is crucial for reliable face recognition systems, yet existing Vision Transformer-based approaches rely exclusively on final-layer representations, ignoring quality-relevant information capt…
Face Image Quality AssessmentFace RecognitionViTNT-FIQA: Training-Free Face Image Quality Assessment with Vision Transformers
Face Image Quality Assessment (FIQA) is essential for reliable face recognition systems. Current approaches primarily exploit only final-layer representations, while training-free methods require multiple forward passes …
Face Image Quality AssessmentComputational EfficiencyFace RecognitionFROQ: Observing Face Recognition Models for Efficient Quality Assessment
Face Recognition (FR) plays a crucial role in many critical (high-stakes) applications, where errors in the recognition process can lead to serious consequences. Face Image Quality Assessment (FIQA) techniques enhance FR…
Face Image Quality AssessmentFace RecognitionA Lightweight Ensemble-Based Face Image Quality Assessment Method with Correlation-Aware Loss
Face image quality assessment (FIQA) plays a critical role in face recognition and verification systems, especially in uncontrolled, real-world environments. Although several methods have been proposed, general-purpose n…
No-Reference Image Quality AssessmentFace Image Quality AssessmentFace RecognitionVQualA 2025 Challenge on Face Image Quality Assessment: Methods and Results
Face images play a crucial role in numerous applications; however, real-world conditions frequently introduce degradations such as noise, blur, and compression artifacts, affecting overall image quality and hindering sub…
Face Image Quality AssessmentViT-FIQA: Assessing Face Image Quality using Vision Transformers
Face Image Quality Assessment (FIQA) aims to predict the utility of a face image for face recognition (FR) systems. State-of-the-art FIQA methods mainly rely on convolutional neural networks (CNNs), leaving the potential…
Face Image Quality AssessmentFace RecognitionMSPT: A Lightweight Face Image Quality Assessment Method with Multi-stage Progressive Training
Accurately assessing the perceptual quality of face images is crucial, especially with the rapid progress in face restoration and generation. Traditional quality assessment methods often struggle with the unique characte…
Face Image Quality AssessmentEfficient Face Image Quality Assessment via Self-training and Knowledge Distillation
Face image quality assessment (FIQA) is essential for various face-related applications. Although FIQA has been extensively studied and achieved significant progress, the computational complexity of FIQA algorithms remai…
Face Image Quality AssessmentKnowledge DistillationDemographic 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+1