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/mabhay3420/Deep-Into-CNN
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/machanic/AU_R-CNN
AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection
https://github.com/maciejdomagala/DLWP_notes
https://github.com/mackitron/COVID19
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/madhavambati/Face-Recognition
https://github.com/maggie0106/Graph-CNN-in-3D-Point-Cloud-Classification
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/magicsunday/pico
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/magnificent1208/r3det-on-mmdetection
https://github.com/mahathi26/ciss
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mahmoodlab/hest
https://github.com/mahxn0/RetinaFace_For_Face_Plate_Detect
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/makatx/YOLO_ResNet
https://github.com/malin9402/2020-0221
https://github.com/malin9402/arcface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/malin9402/retiface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/manankshastri/ART
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/manishravula/yolov3_tiny_pruned
https://github.com/manoranjan03/PaperImplementations
https://github.com/mapooon/PetFace
PetFace: A Large-Scale Dataset and Benchmark for Animal Identification
https://github.com/maragori/DeepfakeForensics-v1
https://github.com/marcin-laskowski/Pulse
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/marcuspearce/MP_FairFace
FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age
https://github.com/marload/ConvNets-TensorFlow2
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/marmara-machine-learning/Facial_Keypoints_NaimishNet_GPU
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/martin220485/everybody_dance_now_pytorch
https://github.com/masoudnick/brain-tumor-mri-classification
https://github.com/matakshay/Neural_Image_Caption_Generator
https://github.com/mathieuorhan/darknet
https://github.com/matlab-deep-learning/mtcnn-face-detection
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/matt-roz/progressive_growing_of_gans_tensorflow_2
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/maxmax1992/WGAN_WGAN-GP
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/maxwelltsai/DeepGalaxy
https://github.com/mayureshpatil30/test-image
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mbsariyildiz/resnet-pytorch
https://github.com/mcbuehler/DeepSEE
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.