https://github.com/KU-CVLAB/MoDiTalker
공식 코드MoDiTalker: Motion-Disentangled Diffusion Model for High-Fidelity Talking Head Generation
Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 25
- 평가표
- 0
- 보존된 평가 기록
- 0
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/KUCognitiveInformaticsLab/PairwiseExpressionAnnotator
공식 코드HAPI: A Model for Learning Robot Facial Expressions from Human Preferences
https://github.com/KaenChan/ProbFace
공식 코드https://github.com/KaimingHe/resnet-1k-layers
공식 코드https://github.com/KamruzzamanAsif/BanglaFake
공식 코드BanglaFake: Constructing and Evaluating a Specialized Bengali Deepfake Audio Dataset
https://github.com/Kartik-3004/facexformer
공식 코드https://github.com/KeqiangSun/FAB
공식 코드FAB: A Robust Facial Landmark Detection Framework for Motion-Blurred Videos
https://github.com/KikimorMay/MultiFace
공식 코드MultiFace: A Generic Training Mechanism for Boosting Face Recognition Performance
https://github.com/KnowledgeDiscovery/FaceSec
공식 코드FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems
https://github.com/KovenYu/state-information
공식 코드Weakly supervised discriminative feature learning with state information for person identification
https://github.com/LSIbabnikz/DifFIQA
공식 코드DifFIQA: Face Image Quality Assessment Using Denoising Diffusion Probabilistic Models
https://github.com/LeiJiangJNU/DAMDNet
공식 코드Dual Attention MobDenseNet(DAMDNet) for Robust 3D Face Alignment
https://github.com/Leminhbinh0209/AAAI22-ADD
공식 코드https://github.com/Leminhbinh0209/KappaFace
공식 코드KappaFace: Adaptive Additive Angular Margin Loss for Deep Face Recognition
https://github.com/LetterLiGo/SafeEar
공식 코드SafeEar: Content Privacy-Preserving Audio Deepfake Detection
https://github.com/Li-Chongyi/Lighting-the-Darkness-in-the-Deep-Learning-Era-Open
공식 코드Low-Light Image and Video Enhancement Using Deep Learning: A Survey
https://github.com/Li-Chongyi/Zero-DCE
공식 코드Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/Li-Wanhua/MetaAge
공식 코드https://github.com/Li-Wanhua/POEs
공식 코드Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression
https://github.com/LonglongaaaGo/EXE-GAN
공식 코드Do Inpainting Yourself: Generative Facial Inpainting Guided by Exemplars
https://github.com/Lotayou/Face-Renovation
공식 코드HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/LynnHo/EigenGAN-Tensorflow
공식 코드https://github.com/MASILab/BRAID
공식 코드Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease
https://github.com/MCG-NJU/SADRNet
공식 코드https://github.com/MIvanovska/MAD-DDPM
공식 코드Face Morphing Attack Detection with Denoising Diffusion Probabilistic Models
https://github.com/MRzzm/DINet
공식 코드DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video
https://github.com/MSoumm/FaVFA
공식 코드Fairer Analysis and Demographically Balanced Face Generation for Fairer Face Verification
https://github.com/MZMMSEC/SJEDD
공식 코드Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approach
https://github.com/MZMMSEC/SO-DFD
공식 코드Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Method
https://github.com/MahmoudRabea13/IdentiFace
공식 코드https://github.com/MarekKowalski/DeepAlignmentNetwork
공식 코드Deep Alignment Network: A convolutional neural network for robust face alignment
https://github.com/MarekKowalski/HoloFace
공식 코드HoloFace: Augmenting Human-to-Human Interactions on HoloLens
https://github.com/Martlgap/btm-stm
공식 코드Susceptibility to Image Resolution in Face Recognition and Trainings Strategies
https://github.com/Martlgap/xqlfw
공식 코드https://github.com/MasoumehSharafi/DSFDA-for-Pain-Assessment
공식 코드Disentangled Source-Free Personalization for Facial Expression Recognition with Neutral Target Data
https://github.com/Media-Smart/vedadet/tree/main/configs/trainval/tinaface
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.