Robust Face Recognition
19 papers with code • 0 benchmarks • 4 datasets
Robust face recognition is the task of performing recognition in an unconstrained environment, where there is variation of view-point, scale, pose, illumination and expression of the face images.
( Image credit: MeGlass dataset )
Benchmarks
These leaderboards are used to track progress in Robust Face Recognition
MALF
UFDD
MeGlass
OCFR-LFW
Latest papers
Embedding Non-Distortive Cancelable Face Template Generation
zamdimon/distortion-generator
•
•
Biometric authentication systems are crucial for security, but developing them involves various complexities, including privacy, security, and achieving high accuracy without directly storing pure biometric data in storage.
SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
serengil/deepface
•
•
IEEE Transactions on Image Processing 2021
Deep face recognition has achieved great success due to large-scale training databases and rapidly developing loss functions.
Complete Face Recovery GAN: Unsupervised Joint Face Rotation and De-Occlusion From a Single-View Image
yeongjoonJu/CFR-GAN
•
•
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2022
In addition, the lack of high-quality paired data remains an obstacle for both methods.
LARNet: Lie Algebra Residual Network for Face Recognition
paradocx/LARNet
•
•
We prove that face rotation in the image space is equivalent to an additive residual component in the feature space of CNNs, which is determined solely by the rotation.
OSTeC: One-Shot Texture Completion
barisgecer/OSTeC
•
•
CVPR 2021
Many recent 3D facial texture reconstruction and pose manipulation from a single image approaches still rely on large and clean face datasets to train image-to-image Generative Adversarial Networks (GANs).
Masked Face Recognition with Latent Part Detection
mindspore-ai/models
•
•
Proceedings of the 28th ACM International Conference on Multimedia 2020
The proposed LPD model is trained in an end-to-end manner and only utilizes the original and synthetic training data.
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
Face image quality is an important factor to enable high performance face recognition systems.
Weakly supervised discriminative feature learning with state information for person identification
KovenYu/state-information
•
•
CVPR 2020
We evaluate our model on unsupervised person re-identification and pose-invariant face recognition.
Face Recognition via Locality Constrained Low Rank Representation and Dictionary Learning
First, a low-rank representation is introduced to handle the possible contamination of the training as well as test data.
Occlusion Robust Face Recognition Based on Mask Learning With Pairwise Differential Siamese Network
Inspired by the fact that human visual system explicitly ignores the occlusion and only focuses on the non-occluded facial areas, we propose a mask learning strategy to find and discard corrupted feature elements from recognition.
