MF2: Level Playing Field for Million Scale Face Recognition(672K people in 4.7M images) [paper] [dataset] [result][benckmark]
MegaFace: The MegaFace Benchmark: 1 Million Faces for Recognition at Scale(690k people in 1M images) [paper][dataset] [result] [benckmark]
UMDFaces: An Annotated Face Dataset for Training Deep Networks(8k people in 367k images with pose, 21 key-points and gender) [paper] [dataset]
MS-Celeb-1M: A Dataset and Benchmark for Large Scale Face Recognition(100K people in 10M images) [paper] [dataset][result] [benchmark] [project]
VGGFace2: A dataset for recognising faces across pose and age(9k people in 3.3M images) [paper] [dataset]
VGGFace: Deep Face Recognition(2.6k people in 2.6M images) [paper] [dataset]
CASIA-WebFace: Learning Face Representation from Scratch(10k people in 500k images) [paper] [dataset]
LFW: Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments(5.7k people in 13k images) [report] [dataset] [result] [benchmark]
Face Detection
WiderFace: WIDER FACE: A Face Detection Benchmark(400k people in 32k images with a high degree of variability in scale, pose and occlusion) [paper] [dataset] [result] [benchmark]
FDDB: A Benchmark for Face Detection in Unconstrained Settings(5k faces in 2.8k images) [report] [dataset] [result][benchmark]
Face Landmark
LS3D-W: A large-scale 3D face alignment dataset constructed by annotating the images from AFLW, 300VW, 300W and FDDB in a consistent manner with 68 points using the automatic method [paper] [dataset]
AFLW: Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization(25k faces with 21 landmarks) [paper] [benchmark]
Face Attribute
CelebA: Deep Learning Face Attributes in the Wild(10k people in 202k images with 5 landmarks and 40 binary attributes per image) [paper] [dataset]
🔖Face Recognition
2018Survey: Deep Facial Expression Recognition: A Survey [paper]
2018Survey: Deep Face Recognition: A Survey [paper]
SphereFace+(MHE): Learning towards Minimum Hyperspherical Energy [paper] [code]
MobileFace: A face recognition solution on mobile device [code]
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices [paper] [code1] [code2][code3] [code4]
FaceID: An implementation of iPhone X's FaceID using face embeddings and siamese networks on RGBD images. [code][blog]
InsightFace(ArcFace): 2D and 3D Face Analysis Project [paper] [code1] [code2]
AAM-Softmax(CCL): Face Recognition via Centralized Coordinate Learning [paper]
AM-Softmax: Additive Margin Softmax for Face Verification [paper] [code1] [code2]
CosFace: Large Margin Cosine Loss for Deep Face Recognition [paper] [code1] [code2]
FeatureIncay: Feature Incay for Representation Regularization [paper]
CocoLoss: Rethinking Feature Discrimination and Polymerization for Large-scale Recognition [paper] [code]
NormFace: L2 hypersphere embedding for face Verification [paper] [code]
SphereFace(A-Softmax): Deep Hypersphere Embedding for Face Recognition [paper] [code]
L-Softmax: Large-Margin Softmax Loss for Convolutional Neural Networks [paper] [code1] [code2] [code3] [code4][code5] [code6] [code7]
CenterLoss: A Discriminative Feature Learning Approach for Deep Face Recognition [paper] [code1] [code2] [code3][code4]
OpenFace: A general-purpose face recognition library with mobile applications [report] [project] [code1] [code2]
FaceNet: A Unified Embedding for Face Recognition and Clustering [paper] [code]
DeepID3: DeepID3: Face Recognition with Very Deep Neural Networks [paper]
DeepID2+: Deeply learned face representations are sparse, selective, and robust [paper]
DeepID2: Deep Learning Face Representation by Joint Identification-Verification [paper]
DeepID: Deep Learning Face Representation from Predicting 10,000 Classes [paper]
DeepFace: Closing the gap to human-level performance in face verification [paper]
LBP+Joint Bayes: Bayesian Face Revisited: A Joint Formulation [paper] [code1] [code2] [code3]
LBPFace: Face recognition with local binary patterns [paper] [code]
FisherFace(LDA): Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection [paper] [code]
EigenFace(PCA): Face recognition using eigenfaces [paper] [code]
🔖Face Detection
HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition [paper] [code]
PyramidBox: A Context-assisted Single Shot Face Detector [paper] [code]
PCN: Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks [paper] [code]
S³FD: Single Shot Scale-invariant Face Detector [paper] [code]
SSH: Single Stage Headless Face Detector [paper] [code]
FaceBoxes: A CPU Real-time Face Detector with High Accuracy [paper][code1] [code2]
MTCNN: Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks [paper] [project][code1] [code2] [code3] [code4] [code5] [code6] [code7]
NPD: A Fast and Accurate Unconstrained Face Detector [paper] [code] [project]
PICO: Object Detection with Pixel Intensity Comparisons Organized in Decision Trees [paper] [code]
libfacedetection: A fast binary library for face detection and face landmark detection in images. [code]
SeetaFaceEngine: SeetaFace Detection, SeetaFace Alignment and SeetaFace Identification [code]
🔖Face Landmark
PRNet: Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network [paper] [code]
LAB: Look at Boundary: A Boundary-Aware Face Alignment Algorithm [paper] [project] [code]
Face-Alignment: How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks) [paper] [project] [code1] [code2]
ERT: One Millisecond Face Alignment with an Ensemble of Regression Trees [paper] [code]
🔖Face GAN
HF-PIM: Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization [paper]
Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs [paper]
GANimation: Anatomically-aware Facial Animation from a Single Image [paper] [project] [code]
