Face Recognition
558 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
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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 with no code
A Parallel Attention Network for Cattle Face Recognition
Thus, we create the first large-scale cattle face recognition dataset, ICRWE, for wild environments.
Cell Variational Information Bottleneck Network
In this work, we propose Cell Variational Information Bottleneck Network (cellVIB), a convolutional neural network using information bottleneck mechanism, which can be combined with the latest feedforward network architecture in an end-to-end training method.
KeyPoint Relative Position Encoding for Face Recognition
By anchoring the significance of pixels around keypoints, the model can more effectively retain spatial relationships, even when those relationships are disrupted by affine transformations.
Hierarchical Generative Network for Face Morphing Attacks
To address the above issues, we propose a novel morphing attack method to improve the quality of morphed images and better preserve the contributing identities.
Generalized Relevance Learning Grassmann Quantization
The proposed model returns a set of prototype subspaces and a relevance vector.
Adaptive Hybrid Masking Strategy for Privacy-Preserving Face Recognition Against Model Inversion Attack
Specifically, face images are masked in the frequency domain using an adaptive MixUp strategy.
VIGFace: Virtual Identity Generation Model for Face Image Synthesis
Initially, we train the face recognition model using a real face dataset and create a feature space for both real and virtual IDs where virtual prototypes are orthogonal to other prototypes.
Rediscovering BCE Loss for Uniform Classification
We also propose the uniform classification accuracy as a metric to measure the model's performance in uniform classification.
Mitigating the Impact of Attribute Editing on Face Recognition
To mitigate this issue, we propose two novel techniques for local and global attribute editing.
Confidence-Aware RGB-D Face Recognition via Virtual Depth Synthesis
2D face recognition encounters challenges in unconstrained environments due to varying illumination, occlusion, and pose.
