Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/RicardooYoung/LatentDistributionAdjusting
https://github.com/RichardMathewsII/YOLBO
https://github.com/RobotEdh/facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/RobotMobile/cv-deep-learning-paper-review
https://github.com/RocketFlash/easy_metric_learning/tree/master/tools
https://github.com/Rohed/ml-1
https://github.com/RomanticWithoutStatus/PFLD-TensorFlow2caffe
https://github.com/RoninTheKid/yessir
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/Rosie-Brigham/sesmeg
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/Rubikplayer/flame-fitting
https://github.com/Rudedaisy/attention-is-all-you-need-pytorch
https://github.com/RudreshVeerkhare/StyleGan
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/RuisongZhou/RetinaFace.pytorch
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/Ruoyiran/DeepID
Deep Learning Face Representation by Joint Identification-Verification
https://github.com/RuoyuChen10/objectdetection-saliency-maps
https://github.com/RuoyuGuo/Visualising-Image-Classification-Models-and-Saliency-Maps
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Ruturaj123/VGG16-Keras
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/RyanWu2233/Style_GAN2_FFHQ
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/SANKHA1/Vehicle-Detection
https://github.com/SBPL-Cruz/perch_pose_sampler
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/SHI-Labs/Neighborhood-Attention-Transformer
https://github.com/SJTU-Thinklab-Det/r3det-on-mmdetection
https://github.com/SSN15/Traffic-sign-recognition-using-deep-learning-and-computer-vision
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/SSusantAchary/FaceDetection-counting-using-MTCNN
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/SY-Xuan/pointnet_paddle
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/Saiyam26/Deep-Pixel-wise-Binary-Supervision
Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
https://github.com/Saiyam26/Face-Anti-Spoofing-using-DeePixBiS
Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
https://github.com/Sakib1263/1DResNet-Builder-KERAS
https://github.com/Sakib1263/1DResNet-KERAS
https://github.com/Sakib1263/DenseNet-1D-2D-Tensorflow-Keras
https://github.com/Sakib1263/ResNet-Model-Builder-KERAS
https://github.com/Sakib1263/ResNet-Model-Builder-Tensorflow-Keras
https://github.com/Sakib1263/ResNet-ResNeXt-1D-2D-Tensorflow-Keras
https://github.com/Sakib1263/ResNet-ResNetv2-ResNeXt-1D-2D-Tensorflow-Keras
https://github.com/Sakib1263/ResNet1D-Model-Builder-KERAS
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.