Learning pose-aware models for pose-invariant face recognition in the wild
We propose a method designed to push the frontiers of unconstrained face recognition in
the wild with an emphasis on extreme out-of-plane pose variations. Existing methods either …
the wild with an emphasis on extreme out-of-plane pose variations. Existing methods either …
Face-specific data augmentation for unconstrained face recognition
We identify two issues as key to developing effective face recognition systems: maximizing
the appearance variations of training images and minimizing appearance variations in test …
the appearance variations of training images and minimizing appearance variations in test …
[HTML][HTML] The Florence multi-resolution 3D facial expression dataset
In the literature, several 3D face datasets have been collected, aiming at advancing the field
of 3D face analysis from different perspectives. Data collection generally follows specific …
of 3D face analysis from different perspectives. Data collection generally follows specific …
Deep 3d morphable model refinement via progressive growing of conditional generative adversarial networks
Abstract 3D face reconstruction from a single 2D image is a fundamental Computer Vision
problem of extraordinary difficulty. Statistical modeling techniques, such as the 3D …
problem of extraordinary difficulty. Statistical modeling techniques, such as the 3D …
Unconstrained face identification using maximum likelihood of distances between deep off-the-shelf features
AV Savchenko, NS Belova - Expert Systems with Applications, 2018 - Elsevier
The paper deals with unconstrained face recognition task for the small sample size problem
based on computation of distances between high-dimensional off-the-shelf features …
based on computation of distances between high-dimensional off-the-shelf features …
Investigating nuisances in DCNN-based face recognition
Face recognition “in the wild” has been revolutionized by the deployment of deep learning-
based approaches. In fact, it has been extensively demonstrated that deep convolutional …
based approaches. In fact, it has been extensively demonstrated that deep convolutional …
A Novel Face Recognition Algorithm for Imbalanced Small Samples.
X Song, S Gao, C Chen, S Wang - Traitement du Signal, 2020 - search.ebscohost.com
Deep learning (DL) has become a hotspot in the research of image recognition. However,
the DL strategy must be trained with lots of samples that are distributed evenly across …
the DL strategy must be trained with lots of samples that are distributed evenly across …
Extended youtube faces: a dataset for heterogeneous open-set face identification
C Ferrari, S Berretti, A Del Bimbo - 2018 24th International …, 2018 - ieeexplore.ieee.org
In this paper, we propose an extension of the famous YouTube Faces (YTF) dataset. In the
YTF dataset, the goal was to state whether two videos contained the same subject or not …
YTF dataset, the goal was to state whether two videos contained the same subject or not …
NCC-Net: Normalized cross correlation based deep matcher with robustness to illumination variations
A Subramaniam, P Balasubramanian… - 2018 IEEE Winter …, 2018 - ieeexplore.ieee.org
The task of matching image patches is a fundamental problem in computer vision. When
sufficiently textured patches are normalized up to similarity transformation, a simple …
sufficiently textured patches are normalized up to similarity transformation, a simple …
Understanding confounding factors in face detection and recognition
Currently, face recognition systems perform at or above human-levels on media captured
under controlled conditions. However, confounding factors such as pose, illumination, and …
under controlled conditions. However, confounding factors such as pose, illumination, and …