https://github.com/yangyucheng000/Paper-4/tree/main/PDOC_mindspore
SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
RetinaFace: Single-stage Dense Face Localisation in the Wild
CenterFace: Joint Face Detection and Alignment Using Face as Point
Optimal Projections for Discriminative Dictionary Learning using the JL-lemma
LAD-RCNN:A Powerful Tool for Livestock Face Detection and Normalization
TAA-GCN: A Temporally Aware Adaptive Graph Convolutional Network for Age Estimation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
RetinaFace: Single-stage Dense Face Localisation in the Wild
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Unifying Identification and Context Learning for Person Recognition
Very Deep Convolutional Networks for Large-Scale Image 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
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
GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
VGGFace2: A dataset for recognising faces across pose and age
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.