Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 25
- 평가표
- 0
- 보존된 평가 기록
- 0
Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mic-dkfz/medicaldetectiontoolkit
https://github.com/miccunifi/scantalk
https://github.com/microsoft/computervision-recipes/blob/master/scenarios/similarity/02_state_of_the_art.ipynb
Classification is a Strong Baseline for Deep Metric Learning
https://github.com/microsoft/fb.resnet.torch
https://github.com/midas-research/text2facegan
Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions
https://github.com/midhun-em/face_recognition_facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mike07026/insightface_20190620
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/mikekestemont/deepscript
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mikelasz/fair-psp
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/mikgur/MADE_CV_1000_facial_landmarks
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks
https://github.com/mindlab-ai/mindcv/blob/main/examples/train_cifar_dynamic.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/resnet.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/vgg.py
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindslab-ai/faceshifter
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/mindslab-ai/hififace
HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping
https://github.com/mindslab-mwc5697/facenet_upload
https://github.com/mindspore-ai/contrib/tree/master/papers/Zero-DCE
Low-Light Image and Video Enhancement Using Deep Learning: A Survey
https://github.com/mindspore-ai/contrib/tree/master/papers/Zero-DCE%2B%2B
Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
https://github.com/mindspore-ai/models/blob/master/official/cv/retinanet/
https://github.com/mindspore-ai/models/blob/master/research/cv/LightCNN/
https://github.com/mindspore-ai/models/blob/master/research/cv/PGAN/
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/mindspore-ai/models/blob/master/research/cv/retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/mindspore-ai/models/blob/master/research/cv/retinanet_resnet152
https://github.com/mindspore-ai/models/tree/master/official/cv/centerface
CenterFace: Joint Face Detection and Alignment Using Face as Point
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet50_quant
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet_thor
https://github.com/mindspore-ai/models/tree/master/official/cv/retinaface_resnet50
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/mindspore-ai/models/tree/master/official/cv/sphereface
https://github.com/mindspore-ai/models/tree/master/official/cv/vgg16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-ai/models/tree/master/research/cv/DeepID
https://github.com/mindspore-ai/models/tree/master/research/cv/ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/mindspore-ai/models/tree/master/research/cv/FaceAttribute
https://github.com/mindspore-ai/models/tree/master/research/cv/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/mindspore-ai/models/tree/master/research/cv/PGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.