https://github.com/petermankowski510/facenet_test
FaceNet: A Unified Embedding for Face Recognition and Clustering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Facial Recognition is the task of making a positive identification of a face in a photo or video image against a pre-existing database of faces. It begins with detection - distinguishing human faces from other objects in the image - and then works on identification of those detected faces.
The state of the art tables for this task are contained mainly in the consistent parts of the task : the face verification and face identification tasks.
<span style="color:grey; opacity: 0.6">( Image credit: Face Verification )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
FaceNet: A Unified Embedding for Face Recognition and Clustering
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
AirFace: Lightweight and Efficient Model for Face Recognition
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
FaceNet: A Unified Embedding for Face Recognition and Clustering
Circle Loss: A Unified Perspective of Pair Similarity Optimization
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
FaceNet: A Unified Embedding for Face Recognition and Clustering
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
FaceNet: A Unified Embedding for Face Recognition and Clustering
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.