Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/prajinkhadka/face_det_check
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/prakashpandey9/Text-Classification-Pytorch
https://github.com/prakharbhardwaj1/emotion-recognition
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
https://github.com/pranavbudhwant/ACVAEGAN
CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training
https://github.com/pranavjadhav001/arcface_inversion
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/prasadsawant5/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/princeton-vl/SimpleView
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/priyavrat-misra/xrays-and-gradcam
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/pshashk/seesaw-facenet
AirFace: Lightweight and Efficient Model for Face Recognition
https://github.com/pszemraj/BoulderAreaDetector
https://github.com/pterhoer/FaceImageQuality
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
https://github.com/pterhoer/FingerprintImageQuality
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
https://github.com/ptran1203/facial_beauty
SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction
https://github.com/pulp-platform/hwpe-tb
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
https://github.com/pulp-platform/pulp
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
https://github.com/pulp-platform/pulpissimo
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
https://github.com/purdue-m2/robust_fairness_withNoisy_labels
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
https://github.com/pwc-1/Paper-9/tree/main/5/wavlm
https://github.com/pwc-1/Paper-9/tree/main/6/Zero-DCE
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/pwc-1/Paper-9/tree/main/6/Zero-DCE%2B%2B
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/pytorch/vision
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/qbxlvnf11/face-detection-MTCNN
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/qianjinhao/circle-loss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/qiaoxiu/facenetRetinaFace
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/qidiso/mobilefacenet-V2
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/qingyujean/Classification-on-imbalanced-data
https://github.com/qiuyu96/carver
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
https://github.com/quangson05dt1/keras_facenet_ver1
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/qubvel/efficientnet
https://github.com/qubvel/resnet_152
https://github.com/qvdang-dev/Facial-Recognition
https://github.com/qvdang-dev/Facial-Recognizance
https://github.com/rafaelmata357/Flower-image-classifier
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/raferguson/CNN-Profile-Picture
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/raghakot/keras-resnet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.