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Awesome-3D-Face-Reconstruction

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# Awesome-3D-Face-Reconstruction

A list of 3D face reconstruction resources. We try to keep it updated every week or two with the latest papers.

## Papers

### 2021

- **[VariTex]** VariTex: Variational Neural Face Textures, ICCV2021, Marcel C. Buhler et al. [[PDF]](https://openaccess.thecvf.com/content/ICCV2021/papers/Buhler_VariTex_Variational_Neural_Face_Textures_ICCV_2021_paper.pdf)[[Code]](https://github.com/mcbuehler/VariTex)
- **[CEST]** Self-Supervised 3D Face Reconstruction via Conditional Estimation, ICCV2021, Y. Wen et al. [[PDF]](https://openaccess.thecvf.com/content/ICCV2021/papers/Wen_Self-Supervised_3D_Face_Reconstruction_via_Conditional_Estimation_ICCV_2021_paper.pdf)[Code]
- **[LHFFT]** Learning High-Fidelity Face Texture Completion Without Complete Face Texture, ICCV2021, J. Kin et al.[[PDF]](https://openaccess.thecvf.com/content/ICCV2021/papers/Kim_Learning_High-Fidelity_Face_Texture_Completion_Without_Complete_Face_Texture_ICCV_2021_paper.pdf) [Code]
- **[SSL-Ray Tracing]** Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing, ICCV2021, A. Dib et al. [[PDF]](https://openaccess.thecvf.com/content/ICCV2021/papers/Dib_Towards_High_Fidelity_Monocular_Face_Reconstruction_With_Rich_Reflectance_Using_ICCV_2021_paper.pdf)[[Code]](https://github.com/abdallahdib/abdallahdib.github.io)
- **[H3D-Net]** H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction, ICCV2021, E. Ramon et al. [[PDF]](https://openaccess.thecvf.com/content/ICCV2021/papers/Ramon_H3D-Net_Few-Shot_High-Fidelity_3D_Head_Reconstruction_ICCV_2021_paper.pdf)[Code]
- **[3DIAS]** 3D Shape Reconstruction with Implicit Algebraic Surfaces, ICCV2021, M. Yavartanoo et al.[[PDF]](https://arxiv.org/pdf/2108.08653)[[Code]](https://github.com/myavartanoo/3DIAS_PyTorch)
- **[INORig]** Riggable 3D Face Reconstruction via In-Network Optimization, CVPR2021, Z. Bai et al. [[PDF]](https://openaccess.thecvf.com/content/CVPR2021/papers/Bai_Riggable_3D_Face_Reconstruction_via_In-Network_Optimization_CVPR_2021_paper.pdf)[[Code]](https://github.com/zqbai-jeremy/INORig)

- **[3DCS]**  3DCaricShop: A Dataset and a Baseline Method for Single-View 3D Caricature Face Reconstruction, CVPR2021, Y. Qiu et al. [[PDF]](https://openaccess.thecvf.com/content/CVPR2021/papers/Qiu_3DCaricShop_A_Dataset_and_a_Baseline_Method_for_Single-View_3D_CVPR_2021_paper.pdf)[Code]

- **[IGARen]** Inverting Generative Adversarial Renderer for Face Reconstruction, CVPR2021, J. Piao et al. [[PDF]](https://openaccess.thecvf.com/content/CVPR2021/papers/Piao_Inverting_Generative_Adversarial_Renderer_for_Face_Reconstruction_CVPR_2021_paper.pdf)[Code]

- **[LMF-IaV]** Learning Complete 3D Morphable Face Models From Images and Videos, CVPR2021, A Tewari et al. [[PDF]](https://openaccess.thecvf.com/content/CVPR2021/papers/R_Learning_Complete_3D_Morphable_Face_Models_From_Images_and_Videos_CVPR_2021_paper.pdf)[Code]

- **[SGAN-AF]** Lifting 2D StyleGAN for 3D-Aware Face Generation, CVPR2021, Y. Shi et al. [[PDF]](https://openaccess.thecvf.com/content/CVPR2021/papers/Shi_Lifting_2D_StyleGAN_for_3D-Aware_Face_Generation_CVPR_2021_paper.pdf)[[Code]](https://github.com/seasonSH/LiftedGAN)

- **[MonR]** Monocular Reconstruction of Neural Face Reflectance Fields, CVPR2021, A. Tewari et al.[[PDF]](https://openaccess.thecvf.com/content/CVPR2021/papers/R_Monocular_Reconstruction_of_Neural_Face_Reflectance_Fields_CVPR_2021_paper.pdf)[Code]

- **[AP-WI]** Learning To Aggregate and Personalize 3D Face From In-the-Wild Photo Collection, CVPR2021, Z. Zhang et al. [[PDF]](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_Learning_To_Aggregate_and_Personalize_3D_Face_From_In-the-Wild_Photo_CVPR_2021_paper.pdf) [Code]

- **[WSPT-3DR]** Weakly-Supervised Photo-realistic Texture Generation for 3D Face Reconstruction, arXiv, X. Yin et al.[[PDF]](https://arxiv.org/pdf/2106.08148)[Code]

- **[FFD-WI]** Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images, arXiv, H. Jung et al.[[PDF]](https://arxiv.org/pdf/2105.14857)[Code]

- **[HFM-SSL]** Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing, arXiv, A. Dib et al.[[PDF]](https://arxiv.org/pdf/2103.15432)[Code]

- **[TOF/TONF]** To fit or not to fit: Model-based Face Reconstruction and Occlusion Segmentation from Weak Supervision, arXiv, C. Li et al. [[PDF]](https://arxiv.org/pdf/2106.09614)[[Code]](https://github.com/unibas-gravis/Occlusion-Robust-MoFA)

- **[Fast-GANFIT]** Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction, arXiv, B. Gecer et al. [[PDF]](https://arxiv.org/pdf/2105.07474)[[Code]](https://github.com/barisgecer/ganfit)

- **[WSM-Face]** Weakly-Supervised Multi-Face 3D Reconstruction, arXiv，J. Zhang et al. [[PDF]](https://arxiv.org/pdf/2101.02000)[[Code]](https://github.com/kalyo-zjl/WM3DR)

- **[U-Net]** Hybrid Approach for 3D Head Reconstruction: Using Neural Networks and Visual Geometry, ICPR2021, O. Bouafif et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9412782)[Code]

- **[JFA-CNN]** Joint Face Alignment and 3D Face Reconstruction with Efficient Convolution Neural Networks, ICPR2021, K. Li et al.[[PDF]](https://ailb-web.ing.unimore.it/icpr/media/slides/11715.pdf)[Code]

- **[Muti-Attribute]** Multi-Attribute Regression Network for Face Reconstruction, ICPR2021, X. Li et al.[[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9412668)[Code]

- **[Real-Time]** Real-Time 3d Face Reconstruction From Single Image Using End-To-End Cnn Regression, ICIP2021, S. Wang et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9506103)[Code]

- **[SADRNet]** SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction, TIP2021, Z. Ruan et al. [[PDF]](https://arxiv.org/pdf/2106.03021)[[Code]](https://github.com/MCG-NJU/SADRNet)

- **[Prior-Guided]** Prior-Guided Multi-View 3D Head Reconstruction, TMM2021, X. Wang et al. [[PDF]](https://arxiv.org/pdf/2107.04277)[Code]

- **[AniDetai-WildI]** Learning an animatable detailed 3D face model from in-the-wild images,  ACMTG2021, Y. Feng et al. [[PDF]](https://dl.acm.org/doi/pdf/10.1145/3450626.3459936)[[Code]](https://deca.is.tue.mpg.de.)

- **[Muti-SSL]** Multi-view self-supervised learning for 3D facial texture reconstruction from single image, IVC2021, X. Zeng et al. [[PDF]](https://www.sciencedirect.com/science/article/pii/S026288562100216X/pdfft?isDTMRedir=true&download=true)[Code]

- **[Multi-Gran]** Multi-Granularity Feature Interaction and Relation Reasoning for 3D Dense Alignment and Face Reconstruction, ICASSP2021, L. LI et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9413649)[[Code]](https://github.com/leilimaster/MFIRRN)

- **[LDR-NPM]** Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model, GM2021, H. Cai et al. [[PDF]](https://arxiv.org/pdf/2004.09190)[[Code]](https://github.com/Juyong/CaricatureFace)

- **[PFR-DRTrac]** Practical Face Reconstruction via Differentiable Ray Tracing, GRF2021, A. Dib et al. [[PDF]](https://arxiv.org/pdf/2101.05356)[Code]

- **[LDet-CNN]** Learning-detailed 3D face reconstruction based on convolutional neural networks from a single image, NCA2021, A. Khan et al.[[PDF]](https://link.springer.com/content/pdf/10.1007/s00521-020-05373-w.pdf)[Code]

- **[E-Aware]** Expression-Aware Face Reconstruction via a Dual-Stream Network, TMM2021, X. Chai et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9392331)[Code]

### 2020

* **[ReDA]** ReDA:Reinforced Differentiable Attribute for 3D Face Reconstruction, CVRP2020, W. Zhu et al.[[PDF]](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhu_ReDAReinforced_Differentiable_Attribute_for_3D_Face_Reconstruction_CVPR_2020_paper.pdf)[Code]

* **[Uncertainty-Aware]** Uncertainty-Aware Mesh Decoder for High Fidelity 3D Face Reconstruction, CVPR2020, G. Lee et al.[[PDF]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Lee_Uncertainty-Aware_Mesh_Decoder_for_High_Fidelity_3D_Face_Reconstruction_CVPR_2020_paper.pdf)[Code]

* **[High-Fidelity]** Towards High-Fidelity 3D Face Reconstruction From In-the-Wild Images Using Graph Convolutional Networks, CVPR2020, J. Lin et al.[[PDF]](https://arxiv.org/pdf/2003.05653)[[Code]](https://github.com/FuxiCV/3D-Face-GCNs)

* **[FaceScape]** FaceScape: A Large-Scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction, CVPR2020, H. Yang et al. [[PDF]](https://arxiv.org/pdf/2003.13989)[[Code]](https://github.com/zhuhao-nju/facescape)

* **[Semi-Supervised]** Semi-Supervised 3D Face Representation Learning From Unconstrained Photo Collections, CVPR2020, Z. Gao et al. [[PDF]](https://openaccess.thecvf.com/content_CVPRW_2020/papers/w21/Gao_Semi-Supervised_3D_Face_Representation_Learning_From_Unconstrained_Photo_Collections_CVPRW_2020_paper.pdf)[Code]

* **[AvatarMe]** AvatarMe: Realistically Renderable 3D Facial Reconstruction "In-the-Wild", CVPR2020, A. Lattas et al. [[PDF]](https://arxiv.org/pdf/2003.13845)[[Code]](https://github.com/lattas/avatarme)

* **[RetinaFace]** RetinaFace: Single-Shot Multi-Level Face Localisation in the Wild, CVPR2020, J. Deng et al. [[PDF]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Deng_RetinaFace_Single-Shot_Multi-Level_Face_Localisation_in_the_Wild_CVPR_2020_paper.pdf)[[Code]](https://github.com/barisbatuhan/FaceDetector)

* **[Towards-FAS]**  Towards Fast, Accurate and Stable 3D Dense Face Alignment，ECCV2020, J. Guo et al.[[PDF]](https://arxiv.org/pdf/2009.09960v2.pdf)[[Code]](https://github.com/cleardusk/3DDFA_V2)

* **[Fine-grained]**  Beyond 3DMM Space: Towards Fine-grained 3D Face Reconstruction, ECCV2020, X. Zhu et al.[[PDF]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123530341.pdf)[[Code]](https://github.com/XiangyuZhu-open/Beyond3DMM)

* **[SSM--Occlusion]** Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency, ECCV2020, J. Shang et al.[[PDF]](https://arxiv.org/pdf/2007.12494v1.pdf)[[Code]](https://github.com/jiaxiangshang/MGCNet)

* **[Personalized]** Personalized Face Modeling for Improved Face Reconstruction and Motion Retargeting, ECCV2020, B. Chaudhuri et al. [[PDF]](https://arxiv.org/pdf/2007.06759)[Code]

* **[GCN]** Faster, Better and More Detailed: 3D Face Reconstruction with Graph Convolutional Networks, ACCV2020, S. Cheng et al.[[PDF]](https://openaccess.thecvf.com/content/ACCV2020/papers/Cheng_Faster_Better_and_More_Detailed_3D_Face_Reconstruction_with_Graph_ACCV_2020_paper.pdf)[Code]

* **[PGNet]** Learning 3D Face Reconstruction with a Pose Guidance Network,  ACCV2020, P. Liu et al. [[PDF]](https://arxiv.org/pdf/2010.04384)[Code]

* **[2D-GANs]** Do 2D GANs Know 3D Shape? Unsupervised 3D shape reconstruction from 2D Image, arXiv, X. Pan et al.[[PDF]](https://arxiv.org/pdf/2011.00844)[[Code]](https://github.com/XingangPan/GAN2Shape)

* **[3DFaceGAN]** 3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation, arXiv, S. Moschoglou et al. [[PDF]](https://arxiv.org/pdf/1905.00307)[Code]

* **[AFR]** Adaptive 3D Face Reconstruction from a Single Image, arXiv, K. Li et al. [[PDF]](https://arxiv.org/pdf/2007.03979)[Code]

* **[Mugshots]** 3D face reconstruction from mugshots: Application to arbitrary view face recognition, Neu2020, J. Liang et al.[[PDF]](https://www.sciencedirect.com/science/article/pii/S0925231220309279/pdfft?isDTMRedir=true&download=true)[Code]

* **[Distinctive  Features]** 3D Face Reconstruction From Single 2D Image Using Distinctive Features, ACCESS2020, H. M. Rehan Afzal et al.[[PDF]](https://ieeexplore.ieee.org/iel7/6287639/8948470/09210569.pdf)[Code]

* **[SSL-Detailed]** Self-Supervised Learning of Detailed 3D Face Reconstruction, TIP2020, Y. Chen et al.[[PDF]](https://arxiv.org/pdf/1910.11791v2.pdf)[[Code]](https://github.com/cyj907/unsupervised-detail-layer)

* **[Robust3D]**  Robust3D: a robust 3D face reconstruction application, NCA2020, Z Lv et al.[[PDF]](https://link.springer.com/content/pdf/10.1007/s00521-019-04380-w.pdf)[Code]

* **[3DFR-Wild]** 3D Face Reconstruction from A Single Image Assisted by 2D Face Images in the Wild, TMM2020, X. Tu et al.[[PDF]](https://arxiv.org/pdf/1903.09359v2.pdf)[[Code]](https://github.com/XgTu/2DASL)

* **[Past-Presnt-Future]** 3D Morphable Face Models—Past, Present, and Future, ACMTG2020, B. Egger et al.[[PDF]](https://arxiv.org/pdf/1909.01815)[[Code]](https://github.com/3d-morphable-models/curated-list-of-awesome-3D-Morphable-Model-software-and-data)

* **[Two-Payhway]** A Novel Two-Pathway Encoder-Decoder Network for 3D Face Reconstruction, ICASSP2020, X. Liu et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9053699)[Code]

* **[DNN]** Dual Neural Networks Coupling Data Regression with Explicit Priors for Monocular 3D Face Reconstruction, TMM2020, X. Fan et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9093203)[Code]

### 2019

* **[GANFIT]** GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction, CVPR2019, B. Gecer et al.[[PDF]](https://arxiv.org/pdf/1902.05978v2.pdf)[[Code]](https://github.com/barisgecer/ganfit)
* **[WSL--I2I]** Accurate 3D Face Reconstruction With Weakly-Supervised Learning: From Single Image to Image Set, CVPR2019, Y. Deng et al. [[PDF]](https://openaccess.thecvf.com/content_CVPRW_2019/papers/AMFG/Deng_Accurate_3D_Face_Reconstruction_With_Weakly-Supervised_Learning_From_Single_Image_CVPRW_2019_paper.pdf)[[Code]](https://github.com/Microsoft/Deep3DFaceReconstruction)
* **[High-Fidelity]** Towards High-Fidelity Nonlinear 3D Face Morphable Model, CVPR2019, L. Tran et al. [[PDF]](https://arxiv.org/pdf/1904.04933v1.pdf)[Code]
* **[MVF-Net]** MVF-Net: Multi-View 3D Face Morphable Model Regression, CVPR2019, F. Wu et al.[[PDF]](https://openaccess.thecvf.com/content_CVPR_2019/papers/Wu_MVF-Net_Multi-View_3D_Face_Morphable_Model_Regression_CVPR_2019_paper.pdf)[Code]
* **[DRL-3DF]** Disentangled Representation Learning for 3D Face Shape， CVPR2019, Z. Jiang et al. [[PDF]](https://arxiv.org/pdf/1902.09887v2.pdf)[[Code]](https://github.com/zihangJiang/DR-Learning-for-3D-Face)
* **[D3DF]** Dense 3D Face Decoding Over 2500FPS: Joint Texture & Shape Convolutional Mesh Decoders, CVPR2019, Y. Zhou et al. [[PDF]](https://arxiv.org/pdf/1904.03525v1.pdf)[Code]
* **[C2FF]** Coarse-to-Fine 3D Face Reconstruction, CVPR2019, L. Galteri et al. [[PDF]](https://openaccess.thecvf.com/content_CVPRW_2019/papers/3D-WidDGET/Leonardo_Galteri_Coarse-to-Fine_3D_Face_Reconstruction_CVPRW_2019_paper.pdf)[Code]
* **[Regress SE]** Learning to Regress 3D Face Shape and Expression From an Image Without 3D Supervision, CVPR2019, S. Sanyal et al. [[PDF]](https://arxiv.org/pdf/1905.06817v1.pdf)[[Code]](https://github.com/soubhiksanyal/RingNet)
* **[MMFace]** MMFace: A Multi-Metric Regression Network for Unconstrained Face Reconstruction, CVPR2019, H. Yi et al. [[PDF]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yi_MMFace_A_Multi-Metric_Regression_Network_for_Unconstrained_Face_Reconstruction_CVPR_2019_paper.pdf)[Code]
* **[DF2Net]** DF2Net: A Dense-Fine-Finer Network for Detailed 3D Face Reconstruction, ICCV2019, X. Zeng et al. [[PDF]](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zeng_DF2Net_A_Dense-Fine-Finer_Network_for_Detailed_3D_Face_Reconstruction_ICCV_2019_paper.pdf)[[Code]](https://github.com/xiaoxingzeng/DF2Net)
* **[3DFace-2DVideos]** 3D Face Shape Regression From 2D Videos with Multi-Reconstruction and Mesh Retrieval, ICCV2019, X. Shao et al. [[PDF]](https://openaccess.thecvf.com/content_ICCVW_2019/papers/3DFAW/Shao_3D_Face_Shape_Regression_From_2D_Videos_with_Multi-Reconstruction_and_ICCVW_2019_paper.pdf)[Code]
* **[DMADNet]** Dual Attention MobDenseNet(DAMDNet) for Robust 3D Face Alignment, ICCV2019, L. Jiang et al. [[PDF]](https://arxiv.org/pdf/1908.11821v1.pdf)[[Code]](https://github.com/LeiJiangJNU/DAMDNet)
* **[FDO-3DMM-GAN** Face De-Occlusion Using 3D Morphable Model and Generative Adversarial Network, ICCV2019, X. Yuan et al. [[PDF]](https://openaccess.thecvf.com/content_ICCV_2019/papers/Yuan_Face_De-Occlusion_Using_3D_Morphable_Model_and_Generative_Adversarial_Network_ICCV_2019_paper.pdf)[Code]
* **[MVF-SNet]** Multi-View 3D Face Reconstruction in the Wild Using Siamese Networks, ICCV2019, E. RAmon et al.  [[PDF]](https://openaccess.thecvf.com/content_ICCVW_2019/papers/3DFAW/Ramon_Multi-View_3D_Face_Reconstruction_in_the_Wild_Using_Siamese_Networks_ICCVW_2019_paper.pdf)[Code]()
* **[Smei-Supervised]** Semi-Supervised Monocular 3D Face Reconstruction With End-to-End Shape-Preserved Domain Transfer, ICCV2019, J. Piao et al. [[PDF]](http://openaccess.thecvf.com/content_ICCV_2019/papers/Piao_Semi-Supervised_Monocular_3D_Face_Reconstruction_With_End-to-End_Shape-Preserved_Domain_Transfer_ICCV_2019_paper.pdf)[Code]
* **[3D-DRSD]** 3D Face Modeling From Diverse Raw Scan Data, ICCV2019, F. Liu et al. [[PDF]](https://arxiv.org/pdf/1902.04943v3.pdf)[[Code]](https://github.com/liuf1990/3DFC)
* **[Alignment-GCN]** 3D Dense Face Alignment via Graph Convolution Networks, arXiv, H. Wei et al. [[PDF]](https://arxiv.org/pdf/1904.05562)[Code]
* **[Cascaded regression]** Cascaded regression using landmark displacement for 3D face reconstruction, PRL2019, F. Wu et al. [[PDF]](https://www.sciencedirect.com/science/article/pii/S0167865518303933/pdfft?md5=a69fa4563235a8c753c6470433d2e0cc&pid=1-s2.0-S0167865518303933-main.pdf)[Code]
* **[Fusion-MLD]** Efficient and Accurate Face Shape Reconstruction by Fusion of Multiple Landmark Databases, ICIP2019, Y. Tian et al.[[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8802934)[Code]
* **[Landmark Updating]** Single View 3D Face Reconstruction with Landmark Updating, MIPR2019, P. Liu et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8695341)[Code]
* **[2D-NeuralNet]** 3D face model reconstructing from its 2D images using neural networks, ATIT2019, O. Aleksandroav et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9030503)[Code]
* **[3DF-Wild-Images]** On Learning 3D Face Morphable Model from In-the-Wild Images, TPAMI2019, L. Tran et al. [[PDF]](https://arxiv.org/pdf/1808.09560v2.pdf)[[Code]](https://github.com/tranluan/Nonlinear_Face_3DMM)
* **[SSB]** A Self-Supervised Bootstrap Method for Single-Image 3D Face Reconstruction, WACV2019, Y. Xing et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8658722)[Code]
* **[2D-germetric]** What does 2D geometric information really tell us about 3D face shape?,  IJCV2019, A. Bas et al. [[PDF]](https://arxiv.org/pdf/1708.06703v3.pdf)[[Code]](https://github.com/waps101/MatlabRenderer)

### 2018

* **[DF-JFR-R]** Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition, CVPR2018, F. Liu et al. [[PDF]](https://arxiv.org/pdf/1803.11366v1)[Code]
* **[RGB-D]** Texture Mapping for 3D Reconstruction With RGB-D Sensor, CVPR2018, Y. Fu et al. [[PDF]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Fu_Texture_Mapping_for_CVPR_2018_paper.pdf)[Code]
* **[Extreme3DFR]** Extreme 3D Face Reconstruction: Seeing Through Occlusions, CVPR2018, A. T. Tran et al. [[PDF]](https://arxiv.org/pdf/1712.05083v2.pdf)[[Code]](https://github.com/anhttran/extreme_3d_faces)
* **[Unsupervised-Training]** Unsupervised Training for 3D Morphable Model Regression, CVPR2018, K. Genova et al. [[PDF]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Genova_Unsupervised_Training_for_CVPR_2018_paper.pdf)[[Code]](https://github.com/google/tf_mesh_renderer)
* **[SP3DFR]** Sparse Photometric 3D Face Reconstruction Guided by Morphable Models, CVPR2018, X. Cao et al.[[PDF]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Sparse_Photometric_3D_CVPR_2018_paper.pdf)[Code]
* **[SSML-250HZ]** Self-Supervised Multi-Level Face Model Learning for Monocular Reconstruction at Over 250 Hz, CVPR2018, A. Terwari et al. [[PDF]](https://arxiv.org/pdf/1712.02859v2.pdf)[Code]
* **[Noliner-3DMM]** Nonlinear 3D Face Morphable Model, CVPR2018, L. Tran et al. [[PDF]](https://arxiv.org/pdf/1804.03786v3.pdf)[[Code]](https://github.com/tranluan/Nonlinear_Face_3DMM)
* **[J3DFR-PMRNet]** Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network, ECCV2018, Y. Feng et al. [[PDF]](https://arxiv.org/pdf/1803.07835v1)[[Code]](https://github.com/YadiraF/PRNet)
* **[G3DF-CMA]** Generating 3D Faces using Convolutional Mesh Autoencoders, ECCV2018, A. Ranjan et al. [[PDF]](https://arxiv.org/pdf/1807.10267v3.pdf)[[Code]](https://github.com/anuragranj/coma)
* **[MobileFace]** MobileFace: 3D Face Reconstruction with Efficient CNN Regression, ECCV2018, N. Chinaev et al.[[PDF]](https://arxiv.org/pdf/1809.08809v1)[[Code]](https://github.com/nchinaev/MobileFace)
* **[MFR-Tracking-Applications]** State of the Art on Monocular 3D Face Reconstruction, Tracking, and Applications,  CGF2018, M. Zollhfer et al. [[PDF]](http://zollhoefer.com/papers/EG18_FaceSTAR/paper.pdf)[Code]
* **[Geometry Details]** 3D Face Reconstruction With Geometry Details From a Single Image, TIP2018, L. Jiang et al. [[PDF]](https://arxiv.org/pdf/1702.05619)[Code]
* **[Muliti-view]** Multi-view 3D face reconstruction with deep recurrent neural networks, IMAVIS2018, P. Dou et al. [[PDF]](https://www.researchgate.net/profile/Pengfei-Dou/publication/322634964_Multi-View_3D_Face_Reconstruction_with_Deep_Recurrent_Neural_Networks/links/5a6584a2a6fdccb61c5803cf/Multi-View-3D-Face-Reconstruction-with-Deep-Recurrent-Neural-Networks.pdf)[Code]
* **[CNN-RealTime]** CNN-Based Real-Time Dense Face Reconstruction with Inverse-Rendered Photo-Realistic Face Images, TPAMI2018, Y. Guo et al. [[PDF]](https://arxiv.org/pdf/1708.00980v3.pdf)[Code]
* **[3DFR-LFI]** 3D Face Reconstruction from Light Field Images: A Model-free Approach, ECCV2018,  M. Feng et al. [[PDF]](https://arxiv.org/pdf/1711.05953v4.pdf)[Code]
* **[HFMFR-UM]** High-Fidelity Monocular Face Reconstruction Based on an Unsupervised Model-Based Face Autoencoder, TPAMI2018, A. Tewari et al. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8496850)[Code]
* **[Low-Resolution]** 3D Face Reconstruction from Low-Resolution Images with Convolutional Neural Networks, ICVIP2018, R. Winkler et al. [[PDF]](https://www.researchgate.net/profile/Chengchao-Qu/publication/332285472_3D_Face_Reconstruction_from_Low-Resolution_Images_with_Convolutional_Neural_Networks/links/5d5e490f299bf1b97cfd090a/3D-Face-Reconstruction-from-Low-Resolution-Images-with-Convolutional-Neural-Networks.pdf)[Code]
* **[ExpNet]** ExpNet: Landmark-Free, Deep, 3D Facial Expressions, FG2018, F. Chang et al. [[PDF]](https://arxiv.org/pdf/1802.00542)[Code]

### 2017

* **[End2End]** End-To-End 3D Face Reconstruction With Deep Neural Networks, CVPR2017, P. Dou et al. [[PDF]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Dou_End-To-End_3D_Face_CVPR_2017_paper.pdf)[Code]
* **[DFR-Single]** Learning Detailed Face Reconstruction From a Single Image, CVPR2017, E. Richardson et al. [[PDF]](https://arxiv.org/pdf/1611.05053)[Code]
* **[Large Pose]** Large Pose 3D Face Reconstruction From a Single Image via Direct Volumetric CNN Regression, CVPR2017, A. S. Jackson et al. [[PDF]](https://arxiv.org/pdf/1703.07834)[[Code]](https://github.com/AaronJackson/vrn)
* **[3DMM-Wild]** 3D Face Morphable Models "In-The-Wild", CVPR2017, J .Booth et al. [[PDF]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Booth_3D_Face_Morphable_CVPR_2017_paper.pdf)[Code]
* **[RRD-3DMM]** Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network, CVPR2017, A. T. Tran et al. [[PDF]](https://arxiv.org/pdf/1612.04904)[[Code]](https://github.com/anhttran/3dmm_cnn)
* **[MoFA]** MoFA: Model-Based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction, ICCV2017, A. Tewari et al. [[PDF]](https://arxiv.org/pdf/1703.10580v2)[[Code]](https://github.com/cecabert/Presentation?utm_source=catalyzex.com)
* **[UFG-I2I]** Unrestricted Facial Geometry Reconstruction Using Image-To-Image Translation, ICCV2017, M. Sela et al. [[PDF]](https://arxiv.org/pdf/1703.10131v2)[[Code]](https://github.com/matansel/pix2vertex)

### Before 2017
* **[3DFR-SD]** 3D Face Reconstruction by Learning from Synthetic Data, INSPEC2016, E. Richardson et al. [[PDF]](https://arxiv.org/pdf/1609.04387v2.pdf)[Code]
* **[SingelReference]** 3D Face Reconstruction from a Single Image Using a Single Reference Face Shape, TPAMI2010, I. Kemelmacher-Shlizerman et al. [[PDF]](https://www.academia.edu/download/43093695/D_Face_Reconstruction_from_a_Single_Imag20160226-11379-4skfk2.pdf)[Code]
* **[QualityMeasures]** Automated 3D Face Reconstruction From Multiple Images Using Quality Measures, CVPR2016, M. Piotraschke et al. [[PDF]](https://openaccess.thecvf.com/content_cvpr_2016/papers/Piotraschke_Automated_3D_Face_CVPR_2016_paper.pdf)[Code]

## Datasets

* **[AFLW](https://paperswithcode.com/dataset/aflw)**
* **[AFLW2000-3D](https://paperswithcode.com/dataset/aflw2000-3d)**
* **[BAM!](https://paperswithcode.com/dataset/bam)**
* **[CelebA](https://paperswithcode.com/dataset/celeba)**
* **[CelebA-HQ](https://paperswithcode.com/dataset/celeba-hq)**
* **[CelebAMask-HQ](https://paperswithcode.com/dataset/celebamask-hq)**
* **[CASIA-WebFace](https://paperswithcode.com/dataset/casia-webface)**
* **[CACD](https://paperswithcode.com/dataset/cacd)**
* **[COMA](https://paperswithcode.com/dataset/coma)**
* **[4DFAB](https://paperswithcode.com/dataset/4dfab)**
* **[FFHQ](https://paperswithcode.com/dataset/ffhq)**
* **[Florence](https://paperswithcode.com/dataset/florence)**
* **[FaceWarehouse](https://paperswithcode.com/dataset/facewarehouse)**
* **[FaceScape](https://paperswithcode.com/dataset/facescape)**
* **[FDDB](https://paperswithcode.com/dataset/fddb)**
* **[FRGC](https://paperswithcode.com/dataset/frgc)**
* **[Helen](https://paperswithcode.com/dataset/helen)**
* **[IJB-A](https://paperswithcode.com/dataset/ijb-a)**
* **[LSUN](https://paperswithcode.com/dataset/lsun)**
* **[LFW](https://paperswithcode.com/dataset/lfw)**
* **[LS3D-W](https://paperswithcode.com/dataset/ls3d-w)**
* **[Multi-PIE](https://paperswithcode.com/dataset/multi-pie)**
* **[NoW Benchmark](https://paperswithcode.com/dataset/now-benchmark)**
* **[UMDFaces](https://paperswithcode.com/dataset/umdfaces)**
* **[VGGFace2](https://paperswithcode.com/dataset/vggface2-1)**
* **[VoxCeleb2](https://paperswithcode.com/dataset/voxceleb2)**
* **[WIDER FACE](https://paperswithcode.com/dataset/wider-face-1)**
* [300W](https://paperswithcode.com/dataset/300w)

## Evaluation Metrics

Awesome-3D-Face-Reconstruction

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