人脸识别 | 论文参考
人脸识别技术资料整理
2019/04/06
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
2019/01/12
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
2018/12/01
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
2018/07/21
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
2018/04/20
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.
2018/03/28
InsightFace(ArcFace): 2D and 3D Face Analysis Project
CosFace: Large Margin Cosine Loss for Deep Face Recognition
?Face Benchmark and Dataset
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]
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
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]
?Face Detection
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]
?Face Landmark
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]
?Face 3D
JFDFMR: Joint Face Detection and Facial Motion Retargeting for Multiple Faces [paper]
?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]
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]
Face Lib&Tool
Dlib [url] [github]
OpenCV [docs] [github]
Face3D [github]
转自 https://github.com/becauseofAI/HelloFace
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