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/trzy/VGG16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ttruty/facial-feature-mouse-control
Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression
https://github.com/tueboesen/Active-Learning
Cost-Effective Active Learning for Deep Image Classification
https://github.com/tueboesen/a-optimal-active-learning
Cost-Effective Active Learning for Deep Image Classification
https://github.com/tungdt92/GFA-CNN
Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing
https://github.com/tuvovan/Zero_DCE_TF
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/tuyentv2009/Face-Recognition-
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/twyunting/Deepfake_Video_Classifier
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/u7javed/Image-Enhancer-via-ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/u7javed/Image-Super-Resolution-Enhancer-via-ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/uclaml/Padam
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/udaya2899/deepfake-detection
Exposing DeepFake Videos By Detecting Face Warping Artifacts
https://github.com/ugail/FaciaIBeautyIEEESKIMA2023
https://github.com/uladzislau-varabei/progressively_growing_gan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/ultralytics/yolov5
https://github.com/umd-fire-coml/2020-Face-Generation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/umgupta/2d-slice-set-networks
https://github.com/umitkacar/ai-edge-computing
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
https://github.com/ung200/thats-what-obama-said
https://github.com/unsky/RetinaNet
https://github.com/unsky/focal-loss
https://github.com/usnistgov/image-classification-resnet50
https://github.com/usnistgov/image-regression-resnet50
https://github.com/utsawk/CarND-Traffic-Sign-Classifier-Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/uw-hai/limeade
https://github.com/v-trungdt21/MaskTheFace
https://github.com/valentingol/GANJax
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/vantupham/darknet
https://github.com/varennes/deep-autoencoder
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/varshaneya/Res-SE-Net
https://github.com/varununleashed/tiny_faces_temp
https://github.com/vayuvegula/kerasModels
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vbonifaci/l1opt
https://github.com/vendyv/CodeSpeedy_Internship
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vgangal101/VGG_models
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.