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3D Face Reconstruction

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하위 태스크: 1
평가표: 9
보존된 평가 기록: 94

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/FuxiCV/3D-Face-GCNs

공식 코드

Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks

https://github.com/FuxiCV/MeInGame

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MeInGame: Create a Game Character Face from a Single Portrait

https://github.com/FuxiVirtualHuman/Write-a-Speaker

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Write-a-speaker: Text-based Emotional and Rhythmic Talking-head Generation

https://github.com/Garsonjw/AdvFAS

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AdvFAS: A robust face anti-spoofing framework against adversarial examples

https://github.com/Gradiant/bob.paper.icb2019.gradgpad

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Generalized Presentation Attack Detection: a face anti-spoofing evaluation proposal

https://github.com/HCIILAB/SCUT-FBP5500-Database-Release

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SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction

https://github.com/HCPLab-SYSU/AUE-CRL

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AU-Expression Knowledge Constrained Representation Learning for Facial Expression Recognition

https://github.com/HCPLab-SYSU/CD-FER-Benchmark

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Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition

https://github.com/HDCVLab/EDFace-Celeb-1M

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EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset

https://github.com/HSE-asavchenko/face-emotion-recognition

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Facial expression and attributes recognition based on multi-task learning of lightweight neural networks

https://github.com/HSE-asavchenko/mobile-visual-preferences

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Preferences Prediction using a Gallery of Mobile Device based on Scene Recognition and Object Detection

https://github.com/Hangz-nju-cuhk/Rotate-and-Render

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Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images

https://github.com/Hangz-nju-cuhk/Talking-Face_PC-AVS

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Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation

https://github.com/HanxunH/Unlearnable-Examples

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Unlearnable Examples: Making Personal Data Unexploitable

https://github.com/Helix-IIIT-Delhi/COFFE-Singing_Voice_Deepfake

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Towards Source Attribution of Singing Voice Deepfake with Multimodal Foundation Models

https://github.com/HeyingGithub/Baseline-project-for-MEGC2020_spotting

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Spotting Macro- and Micro-expression Intervals in Long Video Sequences

https://github.com/HongwenZhang/ECT-FaceAlignment

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Combining Data-driven and Model-driven Methods for Robust Facial Landmark Detection

https://github.com/HuangYG123/CurricularFace

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CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition

https://github.com/HuangYG123/DDL

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Improving Face Recognition from Hard Samples via Distribution Distillation Loss

https://github.com/Hzzone/MTLFace

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When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework

https://github.com/Hzzone/PFA-GAN

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PFA-GAN: Progressive Face Aging with Generative Adversarial Network

https://github.com/IDT-ITI/Adv-XAI-Deepfakes

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Improving the Perturbation-Based Explanation of Deepfake Detectors Through the Use of Adversarially-Generated Samples

https://github.com/InterDigitalInc/HRFAE

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High Resolution Face Age Editing

https://github.com/IrvingMeng/MagFace

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MagFace: A Universal Representation for Face Recognition and Quality Assessment

https://github.com/JDAI-CV/FaceX-Zoo/tree/main/addition_module/DMUE

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Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition

https://github.com/JDAI-CV/faceX-Zoo

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FaceX-Zoo: A PyTorch Toolbox for Face Recognition

https://github.com/JDAI-CV/fast-reid

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FastReID: A Pytorch Toolbox for General Instance Re-identification

https://github.com/JFChi/Understanding-and-Mitigating-Accuracy-Disparity-in-Regression

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Understanding and Mitigating Accuracy Disparity in Regression

https://github.com/JOY-MM/JoyGen

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JoyGen: Audio-Driven 3D Depth-Aware Talking-Face Video Editing

https://github.com/JRConti/EthicalModule_vMF

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Mitigating Gender Bias in Face Recognition Using the von Mises-Fisher Mixture Model

https://github.com/JStehouwer/FFD_CVPR2020

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On the Detection of Digital Face Manipulation

https://github.com/Jasonxu1225/Improved-Lightweight-YOLOv5-for-Face-Mask-Detection

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An Improved Lightweight YOLOv5 Model Based on Attention Mechanism for Face Mask Detection

https://github.com/Jessegator/Audio_robustness_evaluation

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Measuring the Robustness of Audio Deepfake Detectors

https://github.com/Jia1018/GoHD

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GoHD: Gaze-oriented and Highly Disentangled Portrait Animation with Rhythmic Poses and Realistic Expression

https://github.com/JianZhang-chick/EMOdiffhead

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EMOdiffhead: Continuously Emotional Control in Talking Head Generation via Diffusion

https://github.com/JianghaiSCU/Diffusion-Low-Light

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Low-Light Image Enhancement with Wavelet-based Diffusion Models

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.