https://github.com/yangyucheng000/papercode-2/tree/main/LADS-mindspore
LAD-RCNN:A Powerful Tool for Livestock Face Detection and Normalization
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.
LAD-RCNN:A Powerful Tool for Livestock Face Detection and Normalization
TAA-GCN: A Temporally Aware Adaptive Graph Convolutional Network for Age Estimation
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
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
VGGFace2: A dataset for recognising faces across pose and age
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
Progressive Growing of GANs for Improved Quality, Stability, and Variation
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
High-Resolution Representations for Labeling Pixels and Regions
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
Exposing DeepFake Videos By Detecting Face Warping Artifacts
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.