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 with no code
A Unified Weight Learning and Low-Rank Regression Model for Robust Complex Error Modeling
For the structured error caused by occlusions or disguises, we propose a GC function based rank approximation to measure the rank of error matrices.
Collaborative representation-based robust face recognition by discriminative low-rank representation
Collaborative representation based classification (CRC) method is exploited in our proposed method which has closed-form solution.
A Paired Sparse Representation Model for Robust Face Recognition from a Single Sample
In order to account for non-linear variations due to pose, a paired sparse representation model is introduced allowing for joint use of variational information and synthetic face images.
M2FPA: A Multi-Yaw Multi-Pitch High-Quality Dataset and Benchmark for Facial Pose Analysis
In this paper, a new large-scale Multi-yaw Multi-pitch high-quality database is proposed for Facial Pose Analysis (M2FPA), including face frontalization, face rotation, facial pose estimation and pose-invariant face recognition.
Accelerated Variance Reduced Stochastic Extragradient Method for Sparse Machine Learning Problems
Moreover, our theoretical analysis shows that AVR-SExtraGD enjoys the best-known convergence rates and oracle complexities of stochastic first-order algorithms such as Katyusha for both strongly convex and non-strongly convex problems.
Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning
To be more specific, the encoder-decoder structured generator is used to learn a pose disentangled face representation, and the encoder-decoder structured discriminator is tasked to perform real/fake classification, face reconstruction, determining identity and estimating face pose.
Attentional Feature-Pair Relation Networks for Accurate Face Recognition
In this paper, we propose a novel face recognition method, called Attentional Feature-pair Relation Network (AFRN), which represents the face by the relevant pairs of local appearance block features with their attention scores.
Low-Rank Laplacian-Uniform Mixed Model for Robust Face Recognition
Sparse representation based methods have successfully put forward a general framework for robust face recognition through linear reconstruction and sparsity constraints.
Illumination Normalization via Merging Locally Enhanced Textures for Robust Face Recognition
Finally, the local contrast equalization (LCE) is performed on the fused face image to reduce the influence caused by over or under saturated pixel values in highlight or dark regions.
M2FPA: A Multi-Yaw Multi-Pitch High-Quality Database and Benchmark for Facial Pose Analysis
In this paper, a new large-scale Multi-yaw Multi-pitch high-quality database is proposed for Facial Pose Analysis (M2FPA), including face frontalization, face rotation, facial pose estimation and pose-invariant face recognition.
