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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/eth-sri/synthpai

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A Synthetic Dataset for Personal Attribute Inference

https://github.com/eurecom-asp/malafide

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Malafide: a novel adversarial convolutive noise attack against deepfake and spoofing detection systems

https://github.com/eurecom-asp/pc-darts-anti-spoofing

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Partially-Connected Differentiable Architecture Search for Deepfake and Spoofing Detection

https://github.com/eurecom-asp/raw-pc-darts-anti-spoofing

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Raw Differentiable Architecture Search for Speech Deepfake and Spoofing Detection

https://github.com/eurecom-asp/rawgat-st-antispoofing

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End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake Detection

https://github.com/eurecom-fscv/2d-malafide

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2D-Malafide: Adversarial Attacks Against Face Deepfake Detection Systems

https://github.com/eye-tracking-for-physiological-sensing/eyelorin

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Inference-Time Gaze Refinement for Micro-Expression Recognition: Enhancing Event-Based Eye Tracking with Motion-Aware Post-Processing

https://github.com/face3d0725/FaceExtraction

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FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face Extraction

https://github.com/face3d0725/face_de_mask

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Non-Deterministic Face Mask Removal Based On 3D Priors

https://github.com/facebookresearch/KeypointNeRF

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KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints

https://github.com/facebookresearch/detectron

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Focal Loss for Dense Object Detection

https://github.com/fahadshamshad/clip2protect

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CLIP2Protect: Protecting Facial Privacy using Text-Guided Makeup via Adversarial Latent Search

https://github.com/fahadshamshad/deep-facial-privacy-prior

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Makeup-Guided Facial Privacy Protection via Untrained Neural Network Priors

https://github.com/fairdeface/FairDeface

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FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation Methods

https://github.com/fangyini/rmes

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RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz Pyramid

https://github.com/faniamokhayeri/C-GAN

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Cross-Domain Face Synthesis using a Controllable GAN

https://github.com/faniamokhayeri/DSFS

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Domain-Specific Face Synthesis for Video Face Recognition from a Single Sample Per Person

https://github.com/farzad-bz/harmonizing-flows

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Harmonizing Flows: Leveraging normalizing flows for unsupervised and source-free MRI harmonization

https://github.com/fatemejamalii/e2f-net

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E2F-Net: Eyes-to-Face Inpainting via StyleGAN Latent Space

https://github.com/faysal-md/unmasking-deepfake-faces-from-videos-an-explainable-cost-sensitive-deep-learning-approach-ieee2023

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Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach

https://github.com/fbiying87/demographic-bias-visualization

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Towards Explaining Demographic Bias through the Eyes of Face Recognition Models

https://github.com/fbiying87/explainable_fiqa_with_amva

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Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models

https://github.com/fdbtrs/AdaDistill

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AdaDistill: Adaptive Knowledge Distillation for Deep Face Recognition

https://github.com/fdbtrs/ElasticFace

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ElasticFace: Elastic Margin Loss for Deep Face Recognition

https://github.com/fdbtrs/IDiff-Face

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IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Models

https://github.com/fdbtrs/QuantFace

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QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit Quantization

https://github.com/fdbtrs/Self-restrained-Triplet-Loss

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Self-restrained Triplet Loss for Accurate Masked Face Recognition

https://github.com/fdbtrs/Unsupervised-Face-Recognition-using-Unlabeled-Synthetic-Data

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Unsupervised Face Recognition using Unlabeled Synthetic Data

https://github.com/fdbtrs/cr-fiqa

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CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability

https://github.com/fdbtrs/exfacegan

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ExFaceGAN: Exploring Identity Directions in GAN's Learned Latent Space for Synthetic Identity Generation

https://github.com/fdbtrs/masked-face-recognition-kd

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Mask-invariant Face Recognition through Template-level Knowledge Distillation

https://github.com/fdbtrs/mixfacenets

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MixFaceNets: Extremely Efficient Face Recognition Networks

https://github.com/fdbtrs/pocketnet

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PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation

https://github.com/fdbtrs/sface-privacy-friendly-and-accurate-face-recognition-using-synthetic-data

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SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data

https://github.com/fdbtrs/synthetic-face-recognition

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Identity-driven Three-Player Generative Adversarial Network for Synthetic-based Face Recognition

https://github.com/fdnerf/fdnerf

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FDNeRF: Few-shot Dynamic Neural Radiance Fields for Face Reconstruction and Expression Editing

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