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/teemoeric/projet
https://github.com/tejaswigowda/semseg-pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/tencentarc/opencompatible
Towards Universal Backward-Compatible Representation Learning
https://github.com/tensorflow/models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/tensorflow/models/tree/master/research/audioset
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/tensorflow/models/tree/master/research/deeplab
https://github.com/tensorflow/models/tree/master/research/slim
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/tensorpack/tensorpack
https://github.com/tensorpack/tensorpack/tree/master/examples/ResNet
https://github.com/text-machine-lab/transformerpy
https://github.com/textvec/textvec
Inverse-Category-Frequency based supervised term weighting scheme for text categorization
https://github.com/tg-bomze/Face-Depixelizer
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/tgeorgy/mgan
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/thanhhungqb/pyramid-super-resolution
https://github.com/the-super-toys/glimpse-models
https://github.com/thearod5/calorie-predictor
CYBORG: Blending Human Saliency Into the Loss Improves Deep Learning
https://github.com/thenhz/progressive_growing_of_gan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/thongdk8/realtime-facereccpp
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/thu-ml/realsafe
RobFR: Benchmarking Adversarial Robustness on Face Recognition
https://github.com/thughost2/Padam
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/tiagoCuervo/JapaNet
https://github.com/tianhai123/yolov3
https://github.com/timesler/facenet-pytorch
https://github.com/timsainb/GAIA
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/tkuanlun350/Kaggle_Ship_Detection_2018
Training Region-based Object Detectors with Online Hard Example Mining
https://github.com/tmdgus1237/HelloWorld2018-2
https://github.com/tomas-gajarsky/facetorch
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/tomasjakab/imm
Unsupervised Learning of Object Landmarks through Conditional Image Generation
https://github.com/toufiksk/darknet
https://github.com/towhee-io/towhee
https://github.com/townim-faisal/Revisiting-Pixel-Wise-Supervision-for-Face-Anti-Spoofing
https://github.com/trachpro/arcface-tf2
https://github.com/trachpro/insightFace_v2
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/travismyers19/Vulnerable_Buildings
https://github.com/trongnghia00/darknet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.