https://github.com/ibadr/RetinaFace
RetinaFace: Single-stage Dense Face Localisation in the Wild
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/ibendrup/MulticolumnNetwork
https://github.com/icey-zhang/MTCNN_paddle
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/icey-zhang/RetinaFace_paddle
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/idealo/image-super-resolution
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/iiTzFrankie/DCJT
https://github.com/iigroup/mm-celeba-hq-dataset
TediGAN: Text-Guided Diverse Face Image Generation and Manipulation
https://github.com/iitmcvg/Demo-of-face-detection-and-counting-
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/ililily/retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/imkoushik22/Walmart-Hackathon
https://github.com/immuno121/audio_source_classification
https://github.com/interdigitalinc/featurestyleencoder
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/interestingzhuo/foodretreival
https://github.com/irynakostyshyn/A-Style-Based-Generator-Architecture-for-GAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/isaacschaal/SG_training
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/isheunesutembo/TB-Computer-Aided-Diagnosis-Using-Deep-Learning
https://github.com/ishspsy/project
Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape Models
https://github.com/iskandari/darknet
https://github.com/istvanmegyeri/audio_tagging
https://github.com/itanish/Face-Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/itijyou/ademxapp
https://github.com/itsuki8914/ESRGAN-TensorFlow
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/ivanwilliammd/I3DR-Net-Transfer-Learning
https://github.com/ivclab/PAE
https://github.com/ivclab/agegenderLMTCNN
https://github.com/ivclab/cvs
https://github.com/ivychill/insightface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/iwasakishuto/DeepScreening
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/j-nowak/covid-19
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/j-void/ISL_v2v
https://github.com/j3soon/arxiv-utils
https://github.com/jackaduma/nude-detect
https://github.com/jacke121/A-Light-and-Fast-Face-Detector-for-Edge-Devices
https://github.com/jacobgil/pytorch-grad-cam
https://github.com/jadevaibhav/Signature-verification-using-deep-learning
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/jadore801120/attention-is-all-you-need-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.