https://github.com/MindSpore-paper-code-3/code9/tree/main/RetinaFace_ResNet50
RetinaFace: Single-stage Dense Face Localisation in the Wild
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Face reconstruction is the task of recovering the facial geometry of a face from an image.
<span style="color:grey; opacity: 0.6">( Image credit: Microsoft Deep3DFaceReconstruction )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
RetinaFace: Single-stage Dense Face Localisation in the Wild
GANimation: Anatomically-aware Facial Animation from a Single Image
RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference
GANimation: Anatomically-aware Facial Animation from a Single Image
RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference
GSmoothFace: Generalized Smooth Talking Face Generation via Fine Grained 3D Face Guidance
Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition
Circle Loss: A Unified Perspective of Pair Similarity Optimization
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
Very Deep Convolutional Networks for Large-Scale Image Recognition
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
FaceNet: A Unified Embedding for Face Recognition and Clustering
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
Real-world adversarial attack on MTCNN face detection system
Very Deep Convolutional Networks for Large-Scale Image Recognition
Challenges in Representation Learning: A report on three machine learning contests
Unsupervised Part-Based Disentangling of Object Shape and Appearance
Improving Shadow Suppression for Illumination Robust Face Recognition
FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.