https://bitbucket.org/aswathyve/unifieddeceptioncorpus
공식 코드UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception Detection
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://git.unl.edu/ece-unl-images-lab/cross-domain-identification
공식 코드Cross-Domain Identification for Thermal-to-Visible Face Recognition
https://github.com/10ring/laa-net
공식 코드https://github.com/1980x/ABAW2020DMACS
공식 코드https://github.com/1980x/ABAW2021DMACS
공식 코드Affect Expression Behaviour Analysis in the Wild using Consensual Collaborative Training
https://github.com/1980x/CCT
공식 코드https://github.com/1980x/SCAN-CCI-FER
공식 코드https://github.com/1980x/dnfer
공식 코드Dynamic Adaptive Threshold based Learning for Noisy Annotations Robust Facial Expression Recognition
https://github.com/1adrianb/binary-networks-pytorch
공식 코드https://github.com/1adrianb/face-alignment
공식 코드https://github.com/1adrianb/unsupervised-face-representation
공식 코드Pre-training strategies and datasets for facial representation learning
https://github.com/1ho0jin1/osfi-by-finetuning
공식 코드Open-Set Face Identification on Few-Shot Gallery by Fine-Tuning
https://github.com/4qlaa7/GCF
공식 코드GCF: Graph Convolutional Networks for Facial Expression Recognition
https://github.com/ACM-MM-2020-Submission/Submission123
공식 코드https://github.com/AI-secure/GMI-Attack
공식 코드The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks
https://github.com/AI-secure/PSBA
공식 코드Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation
https://github.com/AI-secure/SemanticAdv
공식 코드SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing
https://github.com/AKASH2907/deepfakes_video_classification
공식 코드https://github.com/AaronJackson/vrn
공식 코드Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression
https://github.com/AaronSun2000/MakeupAttack
공식 코드MakeupAttack: Feature Space Black-box Backdoor Attack on Face Recognition via Makeup Transfer
https://github.com/Affectiva/LEGAN_Perceptual_Dataset
공식 코드https://github.com/AiTaif7/Color-Matters-AI-Driven-Exploration-of-Human-Feature-Coloration
공식 코드Colors Matter: AI-Driven Exploration of Human Feature Colors
https://github.com/Akinori-F-Ebihara/SpecDiff-spoofing-detector
공식 코드Specular- and Diffuse-reflection-based Face Spoofing Detection for Mobile Devices
https://github.com/AlfredXiangWu/LightCNN
공식 코드https://github.com/AlfredXiangWu/face_verification_experiment
공식 코드https://github.com/Alpkant/Thermal-to-Visible-Face-Recognition-Using-Deep-Autoencoders
공식 코드https://github.com/AmIAttribute/AmI
공식 코드Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples
https://github.com/AntonFirc/diffusion-deepfake-speech-dataset
공식 코드https://github.com/ApGa/adversarial_deepfakes
공식 코드https://github.com/ArnabKumarRoy02/ResEmoteNet
공식 코드ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion Recognition
https://github.com/BCV-Uniandes/AUNets
공식 코드https://github.com/BR-IDL/PaddleViT
공식 코드Coarse-to-Fine Cascaded Networks with Smooth Predicting for Video Facial Expression Recognition
https://github.com/Baojin-Huang/Webface-OCC
공식 코드https://github.com/BehroozRazeghi/CLUB
공식 코드Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility
https://github.com/BehroozRazeghi/Variational-Leakage
공식 코드Variational Leakage: The Role of Information Complexity in Privacy Leakage
https://github.com/BiDAlab/DiveFace
공식 코드SensitiveNets: Learning Agnostic Representations with Application to Face Images
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.