https://github.com/ptran1203/facial_beauty
SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction
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.
SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction
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FaceNet: A Unified Embedding for Face Recognition and Clustering
Circle Loss: A Unified Perspective of Pair Similarity Optimization
RetinaFace: Single-stage Dense Face Localisation in the Wild
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
FaceNet: A Unified Embedding for Face Recognition and Clustering
Very Deep Convolutional Networks for Large-Scale Image Recognition
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출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.