Face Recognition
25개 벤치마크 · 논문 2,510편 · 이 태스크의 논문 보기 →
Benchmarks
LFW
CFP-FP
CASIA-WebFace+masks
CelebA+masks
MLFW
AgeDB-30
Color FERET
IJB-B
CALFW
MFW+ (M-M)
MFW+ (U-M)
MORPH
mebeblurf
Adience (Online Open Set)
CPLFW
Carl
LFW (Online Open Set)
UHDB31
UND-X1
BTS3.1
CFP-FF
EURECOM
MFR
XQLFW
Most implemented
FaceNet: A Unified Embedding for Face Recognition and Clustering
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
VGGFace2: A dataset for recognising faces across pose and age
SphereFace: Deep Hypersphere Embedding for Face Recognition
A Light CNN for Deep Face Representation with Noisy Labels
Circle Loss: A Unified Perspective of Pair Similarity Optimization
Papers
SynThermFace: Amplifying Limited Paired Data for Visible-Thermal Face Recognition via Synthetic Data Generation
Face recognition (FR) is a widely used modality for biometric authentication, but conventional models rely on visible-spectrum imagery and degrade when high-quality RGB images cannot be captured. Cross-spectral face reco…
Synthetic Data GenerationFace RecognitionA Kernel-Based Modular Discriminant Analysis Framework for Small-Sample Learning
The small-sample-size (SSS) problem remains a fundamental challenge in machine learning when labeled data are scarce due to cost, accessibility, or ethical constraints. While numerous approaches have been proposed, exist…
Hyperspectral Image ClassificationMedical DiagnosisFace RecognitionFault DiagnosisLearning Late, Guiding Early: Timestep-Decoupled Semantic Guidance for Fair Face Generation
Demographic imbalance in synthetic face generation can propagate to downstream face recognition systems, making fairness an important consideration when diffusion models are used for data generation. Existing fairness-aw…
Face RecognitionBreaking High Confidence: Practical Face Impersonation under High-Security Thresholds
Face recognition systems (FRSs) are increasingly deployed in critical real-world services for authentication, such as banking applications and airport identity checks, necessitating stringent security configurations. Con…
Face RecognitionEXPL-FR: Explaining Face Recognition Models via Vision-Language Alignment
Deep face recognition (FR) models reach near-saturated accuracy but remain opaque: a practitioner cannot ask which semantic attributes a similarity score relied upon. EXPL-FR answers this inside the FR model's own embedd…
Face RecognitionSteering the Flow: Inverting Face Recognition Models via Gradient-Guided Flow Matching
Model Inversion Attacks (MIAs) aim to reconstruct representative training samples of target identities from face recognition models, exposing critical security vulnerabilities. Existing methods typically rely on indirect…
Face Recognition