https://github.com/bovifocr/insightface
Sample and Computation Redistribution for Efficient Face Detection
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.
Sample and Computation Redistribution for Efficient Face Detection
FaceNet: A Unified Embedding for Face Recognition and Clustering
A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion
From Facial Parts Responses to Face Detection: A Deep Learning Approach
Few-shot Knowledge Transfer for Fine-grained Cartoon Face Generation
RetinaFace: Single-stage Dense Face Localisation in the Wild
Training Region-based Object Detectors with Online Hard Example Mining
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
MOON: A Mixed Objective Optimization Network for the Recognition of Facial Attributes
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Progressive Growing of GANs for Improved Quality, Stability, and Variation
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection
Progressive Growing of GANs for Improved Quality, Stability, and Variation
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.