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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/aosokin/cnn_head_detection
공식 코드https://github.com/apchenstu/Facial_Details_Synthesis
공식 코드https://github.com/aqeelanwar/MaskTheFace
공식 코드https://github.com/arassadin/emotiw2017
공식 코드Group-level Emotion Recognition using Transfer Learning from Face Identification
https://github.com/aravinda27/extswap
공식 코드ExtSwap: Leveraging Extended Latent Mapper for Generating High Quality Face Swapping
https://github.com/architect-road/icongan
공식 코드Design What You Desire: Icon Generation from Orthogonal Application and Theme Labels
https://github.com/arctrinity9/datasets-reachocc-and-synchocc
공식 코드Self-Supervised Robustifying Guidance for Monocular 3D Face Reconstruction
https://github.com/aria-zhangjl/e3-facenet
공식 코드https://github.com/arin-upna/biased-heritage
공식 코드Biased Heritage: How Datasets Shape Models in Facial Expression Recognition
https://github.com/arkel23/animesion
공식 코드https://github.com/arnesh2212/SocialDF
공식 코드https://github.com/arpitbansal297/universal-guided-diffusion
공식 코드https://github.com/arturjordao/IncrementalDimensionalityReduction
공식 코드Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction Method
https://github.com/aryan-garg/styledcgan
공식 코드https://github.com/asankagp/mod20
공식 코드A Multi-viewpoint Outdoor Dataset for Human Action Recognition
https://github.com/ashafahi/inceptionv3-transferLearn-poison
공식 코드Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
https://github.com/asindel/artfacepoints
공식 코드ArtFacePoints: High-resolution Facial Landmark Detection in Paintings and Prints
https://github.com/asvspoof-challenge/2021
공식 코드ASVspoof 2021: Automatic Speaker Verification Spoofing and Countermeasures Challenge Evaluation Plan
https://github.com/atzoriandrea/Exploratory-Analysis-in-Face-Authentication
공식 코드Explaining Bias in Deep Face Recognition via Image Characteristics
https://github.com/audeering/w2v2-how-to
공식 코드Dawn of the transformer era in speech emotion recognition: closing the valence gap
https://github.com/autonomousvehiclelaboratory/anonymization
공식 코드https://github.com/awslabs/cis-matching-tasks
공식 코드https://github.com/axeber01/dold
공식 코드https://github.com/azadlab/FExGAN
공식 코드https://github.com/azadlab/FExGAN-Meta
공식 코드https://github.com/azgo14/classification_metric_learning
공식 코드Classification is a Strong Baseline for Deep Metric Learning
https://github.com/azrealwang/sgadv
공식 코드Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition
https://github.com/baidu/AdvBox
공식 코드Advbox: a toolbox to generate adversarial examples that fool neural networks
https://github.com/bairdzhang/smallhardface
공식 코드Robust Face Detection via Learning Small Faces on Hard Images
https://github.com/baiyangwang/emgan
공식 코드https://github.com/baoshengyu/H3R
공식 코드https://github.com/barisbatuhan/dass_det_inference
공식 코드Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings
https://github.com/barisbatuhan/dass_detector
공식 코드Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings
https://github.com/barisgecer/OSTeC
공식 코드https://github.com/barisgecer/TBGAN
공식 코드Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.