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/opontorno/dcts_analysis_deepfakes
공식 코드On the Exploitation of DCT-Traces in the Generative-AI Domain
https://github.com/oppo-mente-lab/facescore
공식 코드FaceScore: Benchmarking and Enhancing Face Quality in Human Generation
https://github.com/orchidchetiaphukan/multilingualptm_add_naacl24
공식 코드https://github.com/osamazeeshan/subject-based-domain-adaptation-for-fer
공식 코드Subject-Based Domain Adaptation for Facial Expression Recognition
https://github.com/otroshi/edgeface
공식 코드https://github.com/otroshi/synthdistill
공식 코드SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data
https://github.com/paarthneekhara/facesignsdemo
공식 코드FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes
https://github.com/pablovin/AffectiveMemoryFramework
공식 코드The FaceChannel: A Light-weight Deep Neural Network for Facial Expression Recognition
https://github.com/panasonicconnect/invreg
공식 코드https://github.com/papermsucode/fullbboxrestoration
공식 코드Darker than Black-Box: Face Reconstruction from Similarity Queries
https://github.com/paplhjak/facial-age-estimation-benchmark
공식 코드https://github.com/parham1998/facial-privacy-protection
공식 코드Enhancing Facial Privacy Protection via Weakening Diffusion Purification
https://github.com/parkgeonyeong/dcwp
공식 코드Training Debiased Subnetworks with Contrastive Weight Pruning
https://github.com/parul-gupta/multifakeverse
공식 코드https://github.com/pedrodiamel/ferattention
공식 코드https://github.com/pegahs1993/whisper-afe-talkingheadsgen
공식 코드Comparative Analysis of Audio Feature Extraction for Real-Time Talking Portrait Synthesis
https://github.com/pfilo8/flow-plugin-network-for-conditional-generation
공식 코드https://github.com/ph-w2000/s2pecnet
공식 코드Robust Audio Anti-Spoofing with Fusion-Reconstruction Learning on Multi-Order Spectrograms
https://github.com/phd-research-ai/tca2
공식 코드Transferable Adversarial Face Attack with Text Controlled Attribute
https://github.com/piotrkawa/attack-agnostic-dataset
공식 코드Attack Agnostic Dataset: Towards Generalization and Stabilization of Audio DeepFake Detection
https://github.com/piotrkawa/audio-deepfake-adversarial-attacks
공식 코드Defense Against Adversarial Attacks on Audio DeepFake Detection
https://github.com/piotrkawa/deepfake-whisper-features
공식 코드https://github.com/piotrkawa/specrnet
공식 코드SpecRNet: Towards Faster and More Accessible Audio DeepFake Detection
https://github.com/po0ya/face-magnet
공식 코드https://github.com/polimi-ispl/jpeg-ai-antifor
공식 코드https://github.com/polo5/ldeq_rwr
공식 코드Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models
https://github.com/ppolon/dcp
공식 코드Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition
https://github.com/pratikpv/mri_gan_deepfake
공식 코드MRI-GAN: A Generalized Approach to Detect DeepFakes using Perceptual Image Assessment
https://github.com/prclibo/ice
공식 코드https://github.com/prevso1088/open-set-biometrics
공식 코드https://github.com/prijatelj/bayesian_eval_ground_truth-free
공식 코드A Bayesian Evaluation Framework for Subjectively Annotated Visual Recognition Tasks
https://github.com/protossw512/AdaptiveWingLoss
공식 코드Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression
https://github.com/pterhoer/DeepFakeAnnotations
공식 코드Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
https://github.com/pterhoer/ExplainableFaceImageQuality
공식 코드Pixel-Level Face Image Quality Assessment for Explainable Face Recognition
https://github.com/pterhoer/FairScoreNormalization
공식 코드Post-Comparison Mitigation of Demographic Bias in Face Recognition Using Fair Score Normalization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.