Face Identification

41 papers with code • 4 benchmarks • 5 datasets

Face identification is the task of matching a given face image to one in an existing database of faces. It is the second part of face recognition (the first part being detection). It is a one-to-many mapping: you have to find an unknown person in a database to find who that person is.

Libraries

Use these libraries to find Face Identification models and implementations

Measuring Hidden Bias within Face Recognition via Racial Phenotypes

seymayucer/facialphenotypes 19 Oct 2021

We use the set of observable characteristics of an individual face where a race-related facial phenotype is hence specific to the human face and correlated to the racial profile of the subject.

6
19 Oct 2021

Improvising the Learning of Neural Networks on Hyperspherical Manifold

barulalithb/stereo-angular-margin 29 Sep 2021

First, the stereographic projection is implied to transform data from Euclidean space ($\mathbb{R}^{n}$) to hyperspherical manifold ($\mathbb{S}^{n}$) to analyze the performance of angular margin losses.

1
29 Sep 2021

Facial expression and attributes recognition based on multi-task learning of lightweight neural networks

HSE-asavchenko/face-emotion-recognition 31 Mar 2021

Moreover, it is shown that the usage of our neural network as a feature extractor of facial regions in video frames and concatenation of several statistical functions (mean, max, etc.)

534
31 Mar 2021

Facial expression and attributes recognition based on multi-task learning of lightweight neural networks

HSE-asavchenko/face-emotion-recognition 31 Mar 2021

In this paper, the multi-task learning of lightweight convolutional neural networks is studied for face identification and classification of facial attributes (age, gender, ethnicity) trained on cropped faces without margins.

534
31 Mar 2021

Partial FC: Training 10 Million Identities on a Single Machine

deepinsight/insightface 11 Oct 2020

The experiment demonstrates no loss of accuracy when training with only 10\% randomly sampled classes for the softmax-based loss functions, compared with training with full classes using state-of-the-art models on mainstream benchmarks.

20,946
11 Oct 2020

BroadFace: Looking at Tens of Thousands of People at Once for Face Recognition

kakaoenterprise/BroadFace ECCV 2020

Moreover, we propose a novel compensation method to increase the number of referenced instances in the training stage.

22
15 Aug 2020

Key-Nets: Optical Transformation Convolutional Networks for Privacy Preserving Vision Sensors

visym/keynet 11 Aug 2020

Modern cameras are not designed with computer vision or machine learning as the target application.

17
11 Aug 2020

Deep Polynomial Neural Networks

FaceOnLive/Face-Recognition-SDK-Android 20 Jun 2020

We introduce three tensor decompositions that significantly reduce the number of parameters and show how they can be efficiently implemented by hierarchical neural networks.

201
20 Jun 2020

GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition

SeungyounShin/GroupFace CVPR 2020

In the field of face recognition, a model learns to distinguish millions of face images with fewer dimensional embedding features, and such vast information may not be properly encoded in the conventional model with a single branch.

73
21 May 2020

SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition

raphaelmemmesheimer/sl-dml 23 Apr 2020

Further, we show that our approach generalizes well in experiments on the UTD-MHAD dataset for inertial, skeleton and fused data and the Simitate dataset for motion capturing data.

21
23 Apr 2020