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Robust Face Recognition

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 )

Papers

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Showing 26–50 of 95 papers

TitleStatusHype
Generalized Multi-view Shared Subspace Learning using View Bootstrapping—0
Global Norm-Aware Pooling for Pose-Robust Face Recognition at Low False Positive Rate—0
GoDP: Globally optimized dual pathway system for facial landmark localization in-the-wild—0
High Order Local Directional Pattern Based Pyramidal Multi-structure for Robust Face Recognition—0
Illumination Normalization via Merging Locally Enhanced Textures for Robust Face Recognition—0
Implementation of Robust Face Recognition System Using Live Video Feed Based on CNN—0
Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization—0
Low-Rank Laplacian-Uniform Mixed Model for Robust Face Recognition—0
M2FPA: A Multi-Yaw Multi-Pitch High-Quality Database and Benchmark for Facial Pose Analysis—0
M2FPA: A Multi-Yaw Multi-Pitch High-Quality Dataset and Benchmark for Facial Pose Analysis—0
Median Pixel Difference Convolutional Network for Robust Face Recognition—0
Modal Regression based Atomic Representation for Robust Face Recognition—0
Multi-Path Region-Based Convolutional Neural Network for Accurate Detection of Unconstrained "Hard Faces"—0
Multi-Subregion Based Correlation Filter Bank for Robust Face Recognition—0
Occlusion-guided compact template learning for ensemble deep network-based pose-invariant face recognition—0
On Robust Face Recognition via Sparse Encoding: the Good, the Bad, and the Ugly—0
PAM: Pose Attention Module for Pose-Invariant Face Recognition—0
Peak-Piloted Deep Network for Facial Expression Recognition—0
Pose-invariant face recognition via feature-space pose frontalization—0
Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A—0
Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results—0
Reconstruction-Based Disentanglement for Pose-invariant Face Recognition—0
Regularized Robust Coding for Face Recognition—0
Representation Learning by Rotating Your Faces—0
Robust face recognition based on the wing loss and the _1 regularization—0
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