https://github.com/code-implementation1/Code3/tree/main/FaceRecognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Real-world adversarial attack on MTCNN face detection system
MaskedFace-Net -- A Dataset of Correctly/Incorrectly Masked Face Images in the Context of COVID-19
Progressive Growing of GANs for Improved Quality, Stability, and Variation
PyramidBox++: High Performance Detector for Finding Tiny Face
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Very Deep Convolutional Networks for Large-Scale Image Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors
MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Face Images
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
SeesawFaceNets: sparse and robust face verification model for mobile platform
SeesawFaceNets: sparse and robust face verification model for mobile platform
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.