Face Recognition
556 papers with code • 22 benchmarks • 61 datasets
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.
( Image credit: Face Verification )
Benchmarks
These leaderboards are used to track progress in Face Recognition
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Face Recognition models and implementationsDatasets
LFW
CASIA-WebFace
MS-Celeb-1M
Extended Yale B
MORPH
IJB-B
Adience
VGG Face
RFW
Partial-REID
Subtasks
Latest papers
Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations
Spreadsheets are widely recognized as the most popular end-user programming tools, which blend the power of formula-based computation, with an intuitive table-based interface.
A visualization method for data domain changes in CNN networks and the optimization method for selecting thresholds in classification tasks
In recent years, Face Anti-Spoofing (FAS) has played a crucial role in preserving the security of face recognition technology.
GraFIQs: Face Image Quality Assessment Using Gradient Magnitudes
We propose in this work a novel approach to assess the quality of face images based on inspecting the required changes in the pre-trained FR model weights to minimize differences between testing samples and the distribution of the FR training dataset.
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
Synthetic data is gaining increasing relevance for training machine learning models.
AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge Distillation
To address this problem, we present in this paper a novel knowledge distillation approach, termed AI-KD that can extend on any existing FIQA technique, improving its robustness to alignment variations and, in turn, performance with different alignment procedures.
Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Clues
SPSC and SDSC augment live samples into simulated attack samples by simulating spoofing clues of physical and digital attacks, respectively, which significantly improve the capability of the model to detect "unseen" attack types.
Dealing with Subject Similarity in Differential Morphing Attack Detection
The advent of morphing attacks has posed significant security concerns for automated Face Recognition systems, raising the pressing need for robust and effective Morphing Attack Detection (MAD) methods able to effectively address this issue.
Privacy-Preserving Face Recognition Using Trainable Feature Subtraction
Tencent/TFace
•
•
Recognizable identity features within the image are encouraged by co-training a recognition model on its high-dimensional feature representation.
Arc2Face: A Foundation Model of Human Faces
This paper presents Arc2Face, an identity-conditioned face foundation model, which, given the ArcFace embedding of a person, can generate diverse photo-realistic images with an unparalleled degree of face similarity than existing models.
Continual Forgetting for Pre-trained Vision Models
(i) For unwanted knowledge, efficient and effective deleting is crucial.
