https://github.com/fodark/anonygan
공식 코드Graph-based Generative Face Anonymisation with Pose Preservation
Papers with Code 아카이브
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/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
https://github.com/fuxivirtualhuman/styletalk
공식 코드StyleTalk: One-shot Talking Head Generation with Controllable Speaking Styles
https://github.com/fvmassoli/affwild2-challenge
공식 코드A Multi-resolution Approach to Expression Recognition in the Wild
https://github.com/fvmassoli/cross-resolution-face-recognition
공식 코드https://github.com/fvmassoli/mafer-multires-facial-expression-recognition
공식 코드MAFER: a Multi-resolution Approach to Facial Expression Recognition
https://github.com/fvmassoli/trj-based-adversarials-detection
공식 코드https://github.com/fwang91/IMDb-Face
공식 코드https://github.com/g-milis/NEUTART
공식 코드https://github.com/gabrella/qot
공식 코드Quaternion Orthogonal Transformer for Facial Expression Recognition in the Wild
https://github.com/gama-ufsc/brain-age
공식 코드Does pre-training on brain-related tasks results in better deep-learning-based brain age biomarkers?
https://github.com/gan-police/audiodeepfake-detection
공식 코드https://github.com/gan-police/frequency-forensics
공식 코드https://github.com/gaobb/DLDL
공식 코드https://github.com/garynlfd/kfc
공식 코드KFC: Kinship Verification with Fair Contrastive Loss and Multi-Task Learning
https://github.com/gauravreddy08/OcularAI
공식 코드MagicEye: An Intelligent Wearable Towards Independent Living of Visually Impaired
https://github.com/genbing99/SoftNet-SpotME
공식 코드Shallow Optical Flow Three-Stream CNN for Macro- and Micro-Expression Spotting from Long Videos
https://github.com/germino-liuhe/dsat
공식 코드Precise Facial Landmark Detection by Dynamic Semantic Aggregation Transformer
https://github.com/gewanying/shap-anti-spoofing
공식 코드Explainable deepfake and spoofing detection: an attack analysis using SHapley Additive exPlanations
https://github.com/gilikn/fakeout
공식 코드FakeOut: Leveraging Out-of-domain Self-supervision for Multi-modal Video Deepfake Detection
https://github.com/gist-ailab/teaching-where-to-look
공식 코드https://github.com/git-disl/Chameleon
공식 코드Personalized Privacy Protection Mask Against Unauthorized Facial Recognition
https://github.com/gkaradzhov/ClickbaitRANLP
공식 코드We Built a Fake News & Click-bait Filter: What Happened Next Will Blow Your Mind!
https://github.com/gojasper/flash-diffusion
공식 코드Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation
https://github.com/golnazghiasi/cofw68-benchmark
공식 코드Occlusion Coherence: Detecting and Localizing Occluded Faces
https://github.com/golnazghiasi/hpm-detection-code
공식 코드Occlusion Coherence: Detecting and Localizing Occluded Faces
https://github.com/gongsixue/DebFace
공식 코드Jointly De-biasing Face Recognition and Demographic Attribute Estimation
https://github.com/gonyrosenman/tff
공식 코드https://github.com/grigorisg9gr/deformable_tracking_review_ijcv2016
공식 코드A Comprehensive Performance Evaluation of Deformable Face Tracking "In-the-Wild"
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.