Face Recognition

193 papers with code · Computer Vision

Facial recognition is the task of making a positive identification of a face in a photo or video image against a pre-existing database of faces. It begins with detection - distinguishing human faces from other objects in the image - and then works on identification of those detected faces.

The state of the art tables for this task are contained mainly in the consistent parts of the task : the face verification and face identification tasks.

( Image credit: Face Verification )

Benchmarks

Greatest papers with code

Longitudinal Study of Child Face Recognition

10 Nov 2017davidsandberg/facenet

Face comparison scores are obtained from (i) a state-of-the-art COTS matcher (COTS-A), (ii) an open-source matcher (FaceNet), and (iii) a simple sum fusion of scores obtained from COTS-A and FaceNet matchers.

FACE RECOGNITION

FaceNet: A Unified Embedding for Face Recognition and Clustering

CVPR 2015 davidsandberg/facenet

On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99. 63%.

FACE IDENTIFICATION FACE RECOGNITION FACE VERIFICATION

Partial FC: Training 10 Million Identities on a Single Machine

11 Oct 2020deepinsight/insightface

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.

FACE RECOGNITION REPRESENTATION LEARNING

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

CVPR 2019 deepinsight/insightface

One of the main challenges in feature learning using Deep Convolutional Neural Networks (DCNNs) for large-scale face recognition is the design of appropriate loss functions that enhance discriminative power.

FACE IDENTIFICATION FACE RECOGNITION FACE VERIFICATION

VGGFace2: A dataset for recognising faces across pose and age

23 Oct 2017deepinsight/insightface

The dataset was collected with three goals in mind: (i) to have both a large number of identities and also a large number of images for each identity; (ii) to cover a large range of pose, age and ethnicity; and (iii) to minimize the label noise.

FACE RECOGNITION FACE VERIFICATION IMAGE RETRIEVAL

MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition

27 Jul 2016deepinsight/insightface

In this paper, we design a benchmark task and provide the associated datasets for recognizing face images and link them to corresponding entity keys in a knowledge base.

FACE RECOGNITION IMAGE CAPTIONING

Towards Fast, Accurate and Stable 3D Dense Face Alignment

ECCV 2020 cleardusk/3DDFA

Firstly, on the basis of a lightweight backbone, we propose a meta-joint optimization strategy to dynamically regress a small set of 3DMM parameters, which greatly enhances speed and accuracy simultaneously.

3D FACE RECONSTRUCTION FACE ALIGNMENT FACE RECOGNITION

Improving Face Anti-Spoofing by 3D Virtual Synthesis

2 Jan 2019cleardusk/3DDFA

Specifically, we consider a printed photo as a flat surface and mesh it into a 3D object, which is then randomly bent and rotated in 3D space.

FACE ANTI-SPOOFING FACE RECOGNITION

Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation

26 May 2019ZhaoJ9014/face.evoLVe.PyTorch

Recent deep learning based face recognition methods have achieved great performance, but it still remains challenging to recognize very low-resolution query face like 28x28 pixels when CCTV camera is far from the captured subject.

FACE HALLUCINATION FACE RECOGNITION HETEROGENEOUS FACE RECOGNITION