A comprehensive list of resources for Deep Face Restoartion
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This repository provides a summary of deep learning-based face restoration algorithms. Our classification is based on the review paper "A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact Removal".
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Blind Face Restoration | Face Super-Resolution | Face Deblurring | Face Denoising | Face Artifact Removal |
T. Wang, k. Zhang, X. Chen, W. Luo, J. Deng, T. Lu, X. Cao, W. Liu, H. Li, and S. Zafeiriou “A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact Removal,” arXiv preprint arXiv:2211.02831, 2022. [pdf]
@article{wang2022survey
title={A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact Removal},
author={Wang, Tao, and Zhang, kaihao, and Chen, Xuanxi and Luo, Wenhan and Deng, Jiankang and Lu, Tong and Cao, Xiaochun and Liu, Wei and Li, Hongdong and Zafeiriou, Stefanos},
journal={arXiv preprint arXiv:2211.02831},
year={2022}
}
See our paper for more details. If you have any suggestions, feel free to contact me (e-mail: [email protected]). Thanks.
- Surveys
- Deep Blind Face Restoration
- Deep Face Super-Resolution
- Deep Face Deblurring
- Deep Face Denoising
- Deep Face Artifact Removal
- Other Related Works
- Image Quality Assessment
- Benchmark Datasets
year | Pub | Title | Link |
---|---|---|---|
2012 | CCBR | A Survey of Face Hallucination | [paper] |
2014 | IJCV | A Comprehensive Survey to Face Hallucination | [paper] |
2018 | PR | Super-resolution for biometrics: A comprehensive survey | [paper] |
2018 | CICT | Face Hallucination Techniques: A Survey | [paper] |
2019 | IETIP | Survey on GAN-based Face Hallucination with its Model Development | [paper] |
2020 | CSUR | Deep Learning-based Face Superresolution: A Survey | [paper] |
2022 | Arxiv | A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact Removal | [paper] |
Year | Pub | Title | Links | Arch |
---|---|---|---|---|
2018 | ECCV | Learning Warped Guidance for Blind Face Restoration | [paper][code] | CNN |
2018 | CVPR | FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors | [paper][code] | CNN |
2019 | IJCV | Identity-preserving Face Recovery from Stylized Portraits | [paper][code] | GAN |
2020 | ECCV | Blind Face Restoration via Deep Multi-scale Component Dictionaries | [paper][code] | CNN |
2020 | CVPR | Enhanced Blind Face Restoration with Multi-Exemplar Images and Adaptive Spatial Feature Fusion |
[paper][code] | CNN |
2020 | MM | HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment | [paper][code] | GAN |
2020 | CVPR | Image Processing Using Multi-Code GAN Prior | [paper][code] | GAN |
2021 | TPAMI | Face Restoration via Plug-and-Play 3D Facial Priors | [paper][code] | CNN |
2021 | CVPR | Progressive Semantic-Aware Style Transformation for Blind Face Restoration | [paper][code] | GAN |
2021 | CVPR | Towards Real-World Blind Face Restoration with Generative Facial Prior | [paper][code] | GAN |
2021 | CVPR | GAN Prior Embedded Network for Blind Face Restoration in the Wild | [paper][code] | GAN |
2022 | Arxiv | Multi-prior learning via neural architecture search for blind face restoration | [paper][code] | CNN |
2022 | CVPR | Blind Face Restoration via Integrating Face Shape and Generative Priors | [paper] |
GAN |
2022 | CVPR | RestoreFormer: High-Quality Blind Face Restoration from Undegraded Key-Value Pairs |
[paper][code] | ViT |
2022 | NeurIPS | Towards Robust Blind Face Restoration with Codebook Lookup Transformer | [paper][code] | ViT |
2022 | AAAI | Panini-Net: GAN Prior Based Degradation-Aware Feature Interpolation for Face Restoration | [paper][code] | GAN |
2022 | Arxiv | FaceFormer: Scale-aware Blind Face Restoration with Transformers | [paper][code] | ViT |
2022 | Arxiv | Blind Face Restoration: Benchmark Datasets and a Baseline Model | [paper][code] | ViT |
Year | Pub | Title | Links | Arch |
---|---|---|---|---|
2015 | AAAI | Learning Face Hallucination in the Wild | [paper][code] | CNN |
2016 | ECCV | Deep Cascaded Bi-Network for Face Hallucination | [paper][code] | CNN |
2016 | ECCV | Ultra-Resolving Face Images by Discriminative Generative Networks | [paper][code] | GAN |
2017 | CVPR | Attention-Aware Face Hallucination via Deep Reinforcement Learning | [paper][code] | CNN |
2017 | CVPR | Hallucinating Very Low-Resolution Unaligned and Noisy Face Images by Transformative Discriminative Autoencoders |
[paper][code] | CNN |
2017 | ICCV | Learning to Super-Resolve Blurry Face and Text Images | [paper][code] | GAN |
2017 | AAAI | Face Hallucination with Tiny Unaligned Images by Transformative Discriminative Neural Networks |
[paper][code] | GAN |
2018 | ECCV | Face Super-resolution Guided by Facial Component Heatmaps | [paper][code] | CNN |
2018 | CVPR | Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with gans |
[paper][code] | GAN |
2018 | ECCV | To learn image super-resolution, use a GAN to learn how to do image degradation first |
[paper][code] | GAN |
2019 | CVPRW | Exemplar Guided Face Image Super-Resolution without Facial Landmarks | [paper][code] | CNN |
2019 | BMVC | Progressive Face Super-Resolution via Attention to Facial Landmark | [paper][code] | CNN |
2020 | WACV | Component Attention Guided Face Super-Resolution Network: CAGFace | [paper][code] | CNN |
2020 | TNNLS | Dual-Path Deep Fusion Network for Face Image Hallucination | [paper][code] | CNN |
2019 | NEUCOM | On potentials of regularized Wasserstein generative adversarial networks for realistic hallucination of tiny faces |
[paper][code] | GAN |
2020 | CVPR | PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models |
[paper][code] | GAN |
2021 | TBBIS | E-ComSupResNet: Enhanced Face Super-Resolution Through Compact Network | [paper][code] | CNN |
2021 | MM | Face Hallucination via Split-Attention in Split-Attention Network | [paper][code] | CNN |
2021 | ICIP | Progressive Face Super-Resolution with Non-Parametric Facial Prior Enhancement | [paper][code] | GAN |
2022 | CVPR | GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors |
[paper][code] | GAN |
2022 | ECCV | VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder |
[paper][code] | CNN |
2022 | TPAMI | EDFace-Celeb-1 M: Benchmarking Face Hallucination with a Million-scale Dataset | [paper][code] | CNN |
Year | Pub | Title | Links | Arch |
---|---|---|---|---|
2017 | Arxiv | DeepDeblur: Fast one-step blurry face images restoration | [paper][code] | CNN |
2018 | CVPR | Deep Semantic Face Deblurring | [paper][code] | CNN |
2020 | IJCV | Exploiting Semantics for Face Image Deblurring | [paper][code] | CNN |
2020 | TIP | Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks | [paper][code] | CNN |
2020 | MM | HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment | [paper][code] | GAN |
2020 | AAAI | Learning to deblur face images via sketch synthesis | [paper][code] | CNN |
2022 | TOG | Face Deblurring using Dual Camera Fusion on Mobile Phones | [paper][code] | CNN |
2022 | WACV | Deep Feature Prior Guided Face Deblurring | [paper][code] | CNN |
2022 | Arxiv | Multi-prior learning via neural architecture search for blind face restoration | [paper][code] | CNN |
2022 | Arxiv | Blind Face Restoration: Benchmark Datasets and a Baseline Model | [paper][code] | ViT |
Year | Pub | Title | Links | Arch |
---|---|---|---|---|
2020 | MM | HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment | [paper][code] | GAN |
2022 | Arxiv | Multi-prior learning via neural architecture search for blind face restoration | [paper][code] | CNN |
2022 | Arxiv | Blind Face Restoration: Benchmark Datasets and a Baseline Model | [paper][code] | ViT |
Year | Pub | Title | Links | Arch |
---|---|---|---|---|
2020 | MM | HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment | [paper][code] | GAN |
2022 | Arxiv | Blind Face Restoration: Benchmark Datasets and a Baseline Model | [paper][code] | ViT |
2022 | Arxiv | Multi-prior learning via neural architecture search for blind face restoration | [paper][code] | CNN |
- CG-GAN: Class-Attribute Guided Generative Adversarial Network for Old Photo Restoration, Liu et al., ACMM 2021. Link
- Old Photo Restoration via Deep Latent Space Translation, Wan et al., TPAMI 2022. Link
- Demeshnet: Blind Face Inpainting for Deep Meshface Verification, Zhang et al. TIP 2017. Link
- Face Inpainting based on High-level Facial Attributes, Jampour et al., CVIU 2017. Link
- Autoretouch: Automatic Professional Face Retouching, Shafaei et al., WACV 2021. Link
- Network Architecture Search for Face Enhancement, Yasarla et al., Arxiv 2021. Link
- Towards Automatic Face-to-face Translation, KR, R et al., ACMMM 2019. Link
- A Sketchtransformer Network for Face Photo-sketch Synthesis, Zhu et al., IJCAI 2021. Link
Method | Type | Code/Ref |
---|---|---|
PSNR (Peak Signal-to-Noise Ratio) | Full-Reference | Code |
SSIM (Structural Similarity Index Measurement) | Full-Reference | Code |
MS-SSIM (Multi-scale Structural Similarity Index Measurement) | Full-Reference | Code |
LPIPS (Learned Perceptual Image Patch Similarity) | Full-Reference | Code |
NIQE (Naturalness Image Quality Evaluator) | Non-Reference | Code |
FID (Fréchet Inception Distance) | Non-Reference | Code |
PI (Perceptual Index) | Non-Reference | Code |
MOS (Mean Opinion Score) | Subject-Metric | Ref |
iPrecision | Task Driven-Metric | Ref |
iRecall | Task Driven-Metric | Ref |
LLE (Landmark Localization Error) | Task Driven-Metric | Code |
Deg (Identity Distance) | Task Driven-Metric | Code |
AFLD (Average Face Landmark Distance) | Task Driven-Metric | Code |
AFICS (Average Face ID Cosine Similarity) | Task Driven-Metric | Code |
Dataset | Usage | Quantity | Type |
---|---|---|---|
EDFace-Celeb | training&testing | >1M | paired dataset |
FFHQ | training | 70,000 | non-paired dataset |
CelebChild-Test | testing | 180 | non-paired real-world dataset |
WebPhoto-Test | testing | 407 | non-paired real-world dataset |
LFW-Test | testing | 1,711 | non-paired real-world dataset |