Facial Recognition and Modelling
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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/faysal-md/unmasking-deepfake-faces-from-videos-an-explainable-cost-sensitive-deep-learning-approach-ieee2023
공식 코드Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach
https://github.com/fbiying87/demographic-bias-visualization
공식 코드Towards Explaining Demographic Bias through the Eyes of Face Recognition Models
https://github.com/fbiying87/explainable_fiqa_with_amva
공식 코드https://github.com/fdbtrs/AdaDistill
공식 코드AdaDistill: Adaptive Knowledge Distillation for Deep Face Recognition
https://github.com/fdbtrs/ElasticFace
공식 코드https://github.com/fdbtrs/IDiff-Face
공식 코드IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Models
https://github.com/fdbtrs/QuantFace
공식 코드QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit Quantization
https://github.com/fdbtrs/Self-restrained-Triplet-Loss
공식 코드Self-restrained Triplet Loss for Accurate Masked Face Recognition
https://github.com/fdbtrs/Unsupervised-Face-Recognition-using-Unlabeled-Synthetic-Data
공식 코드Unsupervised Face Recognition using Unlabeled Synthetic Data
https://github.com/fdbtrs/cr-fiqa
공식 코드CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability
https://github.com/fdbtrs/exfacegan
공식 코드https://github.com/fdbtrs/masked-face-recognition-kd
공식 코드Mask-invariant Face Recognition through Template-level Knowledge Distillation
https://github.com/fdbtrs/mixfacenets
공식 코드https://github.com/fdbtrs/pocketnet
공식 코드https://github.com/fdbtrs/sface-privacy-friendly-and-accurate-face-recognition-using-synthetic-data
공식 코드SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data
https://github.com/fdbtrs/synthetic-face-recognition
공식 코드Identity-driven Three-Player Generative Adversarial Network for Synthetic-based Face Recognition
https://github.com/fedeloper/binary_deepfake_detection
공식 코드Faster Than Lies: Real-time Deepfake Detection using Binary Neural Networks
https://github.com/fedenoce/s2l-s2d
공식 코드Learning Landmarks Motion from Speech for Speaker-Agnostic 3D Talking Heads Generation
https://github.com/fei-hdu/ca-gan
공식 코드Towards Realistic Face Photo-Sketch Synthesis via Composition-Aided GANs
https://github.com/fei-hdu/sRender
공식 코드Bridging Unpaired Facial Photos And Sketches By Line-drawings
https://github.com/felixrosberg/facedancer
공식 코드FaceDancer: Pose- and Occlusion-Aware High Fidelity Face Swapping
https://github.com/fengju514/Expression-Net
공식 코드https://github.com/fengju514/Face-Pose-Net
공식 코드https://github.com/fengyuentau/pytorch-flops
공식 코드https://github.com/flakeua/bachelorsthesis
공식 코드Appearance-based gaze estimation enhanced with synthetic images using deep neural networks
https://github.com/flyingby/awesome-deepfake-generation-and-detection
공식 코드https://github.com/fodark/anonygan
공식 코드Graph-based Generative Face Anonymisation with Pose Preservation
https://github.com/forblindrev/aibias
공식 코드Fair and accurate age prediction using distribution aware data curation and augmentation
https://github.com/forever208/fmae-iat
공식 코드Representation Learning and Identity Adversarial Training for Facial Behavior Understanding
https://github.com/forget2save/campro
공식 코드https://github.com/freddiemg/btd--unsupervised-detection-of-medical-deepfakes
공식 코드Back-in-Time Diffusion: Unsupervised Detection of Medical Deepfakes
https://github.com/ftmghorbani/EVI-HRnet
공식 코드Expression-aware video inpainting for HMD removal in XR applications
https://github.com/fudandisc/socioverse
공식 코드https://github.com/fuenwang/mixfairface
공식 코드MixFairFace: Towards Ultimate Fairness via MixFair Adapter in Face Recognition
https://github.com/fusionbrainlab/adversarialfaces
공식 코드Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.