Papers with Code 아카이브
3D Face Reconstruction
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3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/WakingHours-GitHub/EPL
공식 코드https://github.com/Wayfear/Autotune
공식 코드Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues
https://github.com/Weizhi-Zhong/IP_LAP
공식 코드Identity-Preserving Talking Face Generation with Landmark and Appearance Priors
https://github.com/WillHawkins3/deepfakesondemand
공식 코드Deepfakes on Demand: the rise of accessible non-consensual deepfake image generators
https://github.com/WindQingYang/PipeNet
공식 코드PipeNet: Selective Modal Pipeline of Fusion Network for Multi-Modal Face Anti-Spoofing
https://github.com/X-zhangyang/Real-World-Masked-Face-Dataset
공식 코드https://github.com/XiaohangZhan/cdp
공식 코드Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition
https://github.com/YZY-stack/DF40
공식 코드https://github.com/YaN9-Y/lafin
공식 코드https://github.com/YadiraF/DECA
공식 코드Learning an Animatable Detailed 3D Face Model from In-The-Wild Images
https://github.com/YadiraF/PIXIE
공식 코드Collaborative Regression of Expressive Bodies using Moderation
https://github.com/YadiraF/PRNet
공식 코드Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
https://github.com/YangNaruto/FQ-GAN
공식 코드https://github.com/YantaoShen/openBCT
공식 코드https://github.com/YonghaoHe/A-Light-and-Fast-Face-Detector-for-Edge-Devices
공식 코드https://github.com/YoushanZhang/Adversarial-Regression-Learning-for-Bone-Age-Estimation
공식 코드https://github.com/YuYin1/DA-GAN
공식 코드https://github.com/YudongGuo/AD-NeRF
공식 코드AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis
https://github.com/Yushgoel/AdversarialAttack
공식 코드https://github.com/Yuto-Matsunaga/Prompt_Tuning_for_Audio_Deepfake_Detection
공식 코드https://github.com/YuvalNirkin/fsgan
공식 코드https://github.com/ZEISS/iPad_TrueDepth_Issue_App
공식 코드On the Issues of TrueDepth Sensor Data for Computer Vision Tasks Across Different iPad Generations
https://github.com/ZEISS/iPad_TrueDepth_Issue_Eval
공식 코드On the Issues of TrueDepth Sensor Data for Computer Vision Tasks Across Different iPad Generations
https://github.com/ZJU-Brain/OTFPF
공식 코드https://github.com/ZLeopard/PEDCC-Loss
공식 코드A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids
https://github.com/ZamDimon/liveness-detection
공식 코드Cross-Database Liveness Detection: Insights from Comparative Biometric Analysis
https://github.com/ZhaoJ9014/High_Performance_Face_Recognition
공식 코드https://github.com/ZhaoJ9014/face.evoLVe.PyTorch
공식 코드https://github.com/ZhaoxuanWu/Trusted-Maximizers-Entropy-Search-BO
공식 코드Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization
https://github.com/Zheng222/DMFN
공식 코드https://github.com/ZhenghLi/Automated-Detection-of-Equine-Facial-Action-Units
공식 코드https://github.com/ZhiwenShao/ADLD
공식 코드Unconstrained Facial Action Unit Detection via Latent Feature Domain
https://github.com/ZhiwenShao/MCNet-Extension
공식 코드https://github.com/ZhiwenShao/PyTorch-JAANet
공식 코드J$\hat{\text{A}}$A-Net: Joint Facial Action Unit Detection and Face Alignment via Adaptive Attention
https://github.com/ZichenMiao/GNN-with-Low-rank-Learnable-Local-Filters
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.