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
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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
E2F-Net: Eyes-to-Face Inpainting via StyleGAN Latent Space
We further improve the StyleGAN output to find the optimal code in the latent space using a new optimization for GAN inversion technique.
Faceptor: A Generalist Model for Face Perception
This design enhances the unification of model structure while improving application efficiency in terms of storage overhead.
LAFS: Landmark-based Facial Self-supervised Learning for Face Recognition
This enables our method - namely LAndmark-based Facial Self-supervised learning LAFS), to learn key representation that is more critical for face recognition.
Suppress and Rebalance: Towards Generalized Multi-Modal Face Anti-Spoofing
Face Anti-Spoofing (FAS) is crucial for securing face recognition systems against presentation attacks.
Combinatorial Client-Master Multiagent Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing
Task offloading in MEC is a strategy that meets the demands of UDs by distributing tasks between UDs and MEC servers.
Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings
In the realm of security applications, biometric authentication systems play a crucial role, yet one often encounters challenges concerning privacy and security while developing one.
Double Trouble? Impact and Detection of Duplicates in Face Image Datasets
Additional steps based on face recognition and face image quality assessment models reduce false positives, and facilitate the deduplication of the face images both for intra- and inter-subject duplicate sets.
IdentiFace : A VGG Based Multimodal Facial Biometric System
In this paper, we introduce "IdentiFace" which is a multimodal facial biometric system that combines the core of facial recognition with some of the most important soft biometric traits such as gender, face shape, and emotion.
Cross-Age Contrastive Learning for Age-Invariant Face Recognition
Cross-age facial images are typically challenging and expensive to collect, making noise-free age-oriented datasets relatively small compared to widely-used large-scale facial datasets.
Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach
To create a reliable deepfake detection system, four pre-trained Convolutional Neural Network (CNN) models: XceptionNet, InceptionResNetV2, EfficientNetV2S, and EfficientNetV2M were used.
