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Face Recognition
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Facial Recognition is the task of making a positive identification of a face in a photo or video image against a pre-existing database of faces. It begins with detection - distinguishing human faces from other objects in the image - and then works on identification of those detected faces.
The state of the art tables for this task are contained mainly in the consistent parts of the task : the face verification and face identification tasks.
<span style="color:grey; opacity: 0.6">( Image credit: Face Verification )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Attributes Shape the Embedding Space of Face Recognition Models
On the Burstiness of Faces in Set
Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks
SELFI: Selective Fusion of Identity for Generalizable Deepfake Detection
FaceLiVT: Face Recognition using Linear Vision Transformer with Structural Reparameterization For Mobile Device
Balancing Tails when Comparing Distributions: Comprehensive Equity Index (CEI) with Application to Bias Evaluation in Operational Face Biometrics
Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space
ScoreMix: Improving Face Recognition via Score Composition in Diffusion Generators
Towards Large-Scale Pose-Invariant Face Recognition Using Face Defrontalization
Balancing Beyond Discrete Categories: Continuous Demographic Labels for Fair Face Recognition
50 Years of Automated Face Recognition
Leveraging Intermediate Features of Vision Transformer for Face Anti-Spoofing
Efficient Estimation of Regularized Tyler's M-Estimator Using Approximate LOOCV
A Responsible Face Recognition Approach for Small and Mid-Scale Systems Through Personalized Neural Networks
TokBench: Evaluating Your Visual Tokenizer before Visual Generation
Pose-invariant face recognition via feature-space pose frontalization
DiffProb: Data Pruning for Face Recognition
Pura: An Efficient Privacy-Preserving Solution for Face Recognition
Facial Recognition Leveraging Generative Adversarial Networks
StoryReasoning Dataset: Using Chain-of-Thought for Scene Understanding and Grounded Story Generation
MorphGuard: Morph Specific Margin Loss for Enhancing Robustness to Face Morphing Attacks
Test-Time Augmentation for Pose-invariant Face Recognition
DArFace: Deformation Aware Robustness for Low Quality Face Recognition
FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live Images
Automated Visual Attention Detection using Mobile Eye Tracking in Behavioral Classroom Studies
MoDE: Mixture of Diffusion Experts for Any Occluded Face Recognition
Leveraging Simultaneous Usage of Edge GPU Hardware Engines for Video Face Detection and Recognition
Edge-GPU Based Face Tracking for Face Detection and Recognition Acceleration
Person Recognition at Altitude and Range: Fusion of Face, Body Shape and Gait
Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples
Learning Knowledge-based Prompts for Robust 3D Mask Presentation Attack Detection
Learning Unknown Spoof Prompts for Generalized Face Anti-Spoofing Using Only Real Face Images
GIF: Generative Inspiration for Face Recognition at Scale
Transforming faces into video stories -- VideoFace2.0
Explainable Face Recognition via Improved Localization
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