https://github.com/Nacriema/Robust_Face_Recognition
Improving Shadow Suppression for Illumination Robust Face Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Face Verification is a machine learning task in computer vision that involves determining whether two facial images belong to the same person or not. The task involves extracting features from the facial images, such as the shape and texture of the face, and then using these features to compare and verify the similarity between the images.
<span style="color:grey; opacity: 0.6">( Image credit: Pose-Robust Face Recognition via Deep Residual Equivariant Mapping )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Improving Shadow Suppression for Illumination Robust Face Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
RetinaFace: Single-stage Dense Face Localisation in the Wild
VGGFace2: A dataset for recognising faces across pose and age
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
RetinaFace: Single-stage Dense Face Localisation in the Wild
RetinaFace: Single-stage Dense Face Localisation in the Wild
RetinaFace: Single-stage Dense Face Localisation in the Wild
FaceNet: A Unified Embedding for Face Recognition and Clustering
Deep Learning Face Representation by Joint Identification-Verification
FaceCoresetNet: Differentiable Coresets for Face Set Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
RetinaFace: Single-stage Dense Face Localisation in the Wild
Deep Learning Face Representation by Joint Identification-Verification
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
GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition
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.