Face Technology Repository(Updating)
- ISRN: Improved Selective Refinement Network for Face Detection
- DSFD: Dual Shot Face Detector
- PyramidBox++: High Performance Detector for Finding Tiny Face
- VIM-FD: Robust and High Performance Face Detector
- SHF: Robust Face Detection via Learning Small Faces on Hard Images
- SRN: Selective Refinement Network for High Performance Face Detection
- SFDet: Single-Shot Scale-Aware Network for Real-Time Face Detection Robust Face Detection via Learning Small Faces on Hard Images
- JFDFMR: Joint Face Detection and Facial Motion Retargeting for Multiple Faces
- PFLD: A Practical Facial Landmark Detector
- LinkageFace: Linkage Based Face Clustering via Graph Convolution Network
- MLT: Face Recognition: A Novel Multi-Level Taxonomy based Survey
- GhostVLAD: GhostVLAD for set-based face recognition
- DocFace+: ID Document to Selfie Matching
- DiF: Diversity in Faces
- 2018Survey: Face Recognition: From Traditional to Deep Learning Methods
- 2018Survey: Deep Facial Expression Recognition: A Survey
- 2018Survey: Deep Face Recognition: A Survey
- SphereFace+(MHE): Learning towards Minimum Hyperspherical Energy
- HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition
- FRVT: Face Recognition Vendor Test
- GANimation: Anatomically-aware Facial Animation from a Single Image
- StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
- Faceswap: A tool that utilizes deep learning to recognize and swap faces in pictures and videos
- HF-PIM: Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization
- PRNet: Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
- LAB: Look at Boundary: A Boundary-Aware Face Alignment Algorithm
- Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs
- Face-Alignment: How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)
- Face3D: Python tools for processing 3D face
- IMDb-Face: The Devil of Face Recognition is in the Noise
- AAM-Softmax(CCL): Face Recognition via Centralized Coordinate Learning
- AM-Softmax: Additive Margin Softmax for Face Verification
- FeatureIncay: Feature Incay for Representation Regularization
- NormFace: L2 hypersphere embedding for face Verification
- CocoLoss: Rethinking Feature Discrimination and Polymerization for Large-scale Recognition
- L-Softmax: Large-Margin Softmax Loss for Convolutional Neural Networks
- MobileFace: A face recognition solution on mobile device
- Trillion Pairs: Challenge 3: Face Feature Test/Trillion Pairs
- MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
- PyramidBox: A Context-assisted Single Shot Face Detector
- PCN: Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks
- S³FD: Single Shot Scale-invariant Face Detector
- SSH: Single Stage Headless Face Detector
- NPD: A Fast and Accurate Unconstrained Face Detector
- PICO: Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
- libfacedetection: A fast binary library for face detection and face landmark detection in images.
- SeetaFaceEngine: SeetaFace Detection, SeetaFace Alignment and SeetaFace Identification.
- FaceID: An implementation of iPhone X's FaceID using face embeddings and siamese networks on RGBD images.
- InsightFace(ArcFace): 2D and 3D Face Analysis Project
- CosFace: Large Margin Cosine Loss for Deep Face Recognition
- DiF: Diversity in Faces [project] [blog]
- FRVT: Face Recognition Vendor Test [project] [leaderboard]
- IMDb-Face: The Devil of Face Recognition is in the Noise(59k people in 1.7M images) [paper] [dataset]
- Trillion Pairs: Challenge 3: Face Feature Test/Trillion Pairs(MS-Celeb-1M-v1c with 86,876 ids/3,923,399 aligned images + Asian-Celeb 93,979 ids/2,830,146 aligned images) [benckmark] [dataset] [result]
- 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]
- 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]
- 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]
- CelebA: Deep Learning Face Attributes in the Wild(10k people in 202k images with 5 landmarks and 40 binary attributes per image) [paper] [dataset]
- LinkageFace: Linkage Based Face Clustering via Graph Convolution Network [paper]
- MLT: Face Recognition: A Novel Multi-Level Taxonomy based Survey [paper]
- GhostVLAD: GhostVLAD for set-based face recognition [paper]
- DocFace+: ID Document to Selfie Matching [paper] [code]
- 2018Survey: Face Recognition: From Traditional to Deep Learning Methods [paper]
- 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]
- ISRN: Improved Selective Refinement Network for Face Detection [paper]
- DSFD: Dual Shot Face Detector [paper] [code]
- PyramidBox++: High Performance Detector for Finding Tiny Face [paper]
- VIM-FD: Robust and High Performance Face Detector [paper]
- SHF: Robust Face Detection via Learning Small Faces on Hard Images [paper] [code]
- SRN: Selective Refinement Network for High Performance Face Detection [paper]
- SFDet: Single-Shot Scale-Aware Network for Real-Time Face Detection [paper]
- 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]
- TinyFace: Finding Tiny Faces [paper] [project] [code1] [code2] [code3]
- 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]
- PFLD: A Practical Facial Landmark Detector [paper] [project] [code]
- 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]
- JFDFMR: Joint Face Detection and Facial Motion Retargeting for Multiple Faces [paper]
- 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]
- StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation [paper] [code]
- PGAN: Progressive Growing of GANs for Improved Quality, Stability, and Variation [paper] [code1] [code2]
- Faceswap: A tool that utilizes deep learning to recognize and swap faces in pictures and videos [code1] [code2]