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/rnradon/gender_emotion_classification
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/robertofranceschi/Image-classification-on-Caltech101-using-CNNs
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/rockstar-0000/lip_sync_test
A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild
https://github.com/rohanbhutani1993/GeneratingDeepfakes
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/rohansuresh27/FaceNet_face_verification
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/rohith2506/facedetect
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/rohithv/Grammatical-facial-expression-recognition
Grammatical facial expression recognition using customized deep neural network architecture
https://github.com/romaintha/pytorch_pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/ronghuaiyang/arcface-pytorch
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/ronny3050/AdvFaces
https://github.com/roomylee/self-attentive-emb-tf
https://github.com/roscibely/gender-prediction
Predicting Gender by First Name Using Character-level Machine Learning
https://github.com/roshankoirala/Fire_Detection_Model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/rosinality/progressive-gan-pytorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/rowerliu/adbd
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/rowerliu/add
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/roysai/Humpback-whale-identity-challenge
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/rtanno21609/AdaptiveNeuralTrees
https://github.com/ruidaniel/rbaca
https://github.com/ruinmessi/RFBNet
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/run-youngjoo/SC-FEGAN
SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color
https://github.com/rupaai/60DaysOfUdacity
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/ry/tensorflow-resnet
https://github.com/ryanwebster90/gen-overfitting-latent-recovery
Detecting Overfitting of Deep Generative Networks via Latent Recovery
https://github.com/ryubidragonfire/mydarknet
https://github.com/s3nh/unet-midv500
https://github.com/saaries/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/saber2011/darknet
https://github.com/saednasir/Helmet_Yolo
https://github.com/sagnik1511/Transfer-Learning-with-Python
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/sagpant/3dmm_cnn
Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
https://github.com/sahilunagar/VGG16-model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/saiamrit/Facenet-pytorch
https://github.com/saic-fi/bayesian-prompt-learning
https://github.com/saikrishnadas/ResNet-Pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.