3D Face Modelling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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
https://github.com/BiDAlab/mEBAL
공식 코드mEBAL: A Multimodal Database for Eye Blink Detection and Attention Level Estimation
https://github.com/Bingwen-Hu/ERGAN-Pytorch
공식 코드https://github.com/BradyFU/DVG
공식 코드Dual Variational Generation for Low-Shot Heterogeneous Face Recognition
https://github.com/Breakend/BayesianPolicyGradients
공식 코드Bayesian Policy Gradients via Alpha Divergence Dropout Inference
https://github.com/Breakend/OptionGAN
공식 코드https://github.com/Breakend/ReproducibilityInContinuousPolicyGradientMethods
공식 코드Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control
https://github.com/CPS-TUWien/racing_dreamer
공식 코드Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing
https://github.com/Carlyx/DPE
공식 코드DPE: Disentanglement of Pose and Expression for General Video Portrait Editing
https://github.com/ChenqiKONG/OSDFD
공식 코드Open-Set Deepfake Detection: A Parameter-Efficient Adaptation Method with Forgery Style Mixture
https://github.com/ChristosKap/multi_timescale_replay
공식 코드Continual Reinforcement Learning with Multi-Timescale Replay
https://github.com/ClaudiaShu/SSL-FER
공식 코드Revisiting Self-Supervised Contrastive Learning for Facial Expression Recognition
https://github.com/Clench/TAR_resAE
공식 코드TAR: Generalized Forensic Framework to Detect Deepfakes using Weakly Supervised Learning
https://github.com/Cmeo97/MAIF
공식 코드https://github.com/CodeShareBot/Micro-Attention-for-Micro-Expression
공식 코드https://github.com/ControlNet/LAV-DF
공식 코드https://github.com/ControlNet/MARLIN
공식 코드MARLIN: Masked Autoencoder for facial video Representation LearnINg
https://github.com/Coral79/CDDB
공식 코드A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials
https://github.com/Cranial-XIX/DualSMC
공식 코드DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs
https://github.com/CreativePapers/Learn-to-Synthesize-and-Synthesize-to-Learn
공식 코드https://github.com/D-X-Y/SAN
공식 코드https://github.com/D-X-Y/landmark-detection
공식 코드Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection
https://github.com/DLR-RM/stable-baselines3
공식 코드https://github.com/DSC-SPIDAL/rankpredictor
공식 코드https://github.com/DSobscure/cgi_drl_platform
공식 코드An Unsupervised Video Game Playstyle Metric via State Discretization
https://github.com/Darg-Iztech/gender-prediction-from-tweets
공식 코드Gender Prediction from Tweets: Improving Neural Representations with Hand-Crafted Features
https://github.com/DariusAf/MesoNet
공식 코드https://github.com/Data-Science-in-Mechanical-Engineering/cheq
공식 코드Contextualized Hybrid Ensemble Q-learning: Learning Fast with Control Priors
https://github.com/Davidzhangyuanhan/CelebA-Spoof
공식 코드CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotations
https://github.com/DengPingFan/Scoot
공식 코드Face Sketch Synthesis Style Similarity:A New Structure Co-occurrence Texture Measure
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.