awesome-3D-Face

A curated list of awesome 3D Face resources(code and paper)

Morphable Models:

Google Group

• Google group to help foster a research community interested in 3DMMs, share resources etc.: https://groups.google.com/forum/#!forum/3d-morphable-models

Face Models:

• Basel Face Model 2009: http://faces.cs.unibas.ch/bfm/?nav=1-0&id=basel_face_model
• Basel Face Model 2017: http://faces.cs.unibas.ch/bfm/bfm2017.html
• Large Scale 3D Morphable Model: https://xip.uclb.com/i/healthcare_tools/LSFM.html
• Liverpool-York Head Model: https://www-users.cs.york.ac.uk/~nep/research/LYHM/
• Multilinear Autoencoder for 3D Face Model Learning: http://mae.gforge.inria.fr/
• Statistical 3D Shape Models of Human Faces: http://facepage.gforge.inria.fr/
• Surrey Face Model https://cvssp.org/facemodel
• Articulated Expressive Head Model (FLAME): http://flame.is.tue.mpg.de/
• Convolutional Mesh Autoencoder (CoMA): http://coma.is.tue.mpg.de/

Model adaptation to images or videos:

Faces:

• 2DASL: Joint 3D Face Reconstruction and Dense Face Alignment from A Single Image with 2D-Assisted Self-Supervised Learning [paper] [code]
• MVF-Net: Multi-View 3D Face Morphable Model Regression [paper] [code]
• Dense 3D Face Decoding Over 2500FPS: Joint Texture & Shape Convolutional Mesh Decoders [paper]
• Towards High-Fidelity Nonlinear 3D Face Morphable Model [paper] [project]
• Combining 3D Morphable Models: A Large Scale Face-And-Head Model [paper]
• Disentangled Representation Learning for 3D Face Shape [paper] [code]
• Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking [paper]
• MMFace: A Multi-Metric Regression Network for Unconstrained Face Reconstruction [paper]
• RingNet: Learning to Regress 3D Face Shape and Expression From an Image Without 3D Supervision [paper] [code] [project]
• Boosting Local Shape Matching for Dense 3D Face Correspondence [paper]
• FML: Face Model Learning From Videos [paper]
• 3D Morphable Model fitting using edge features: https://github.com/waps101/3DMM_edges
• Basic 3D Morphable Model fitting: https://github.com/anhttran/3dmm_basic
• A lightweight 3D Morphable Model fitting library: https://github.com/patrikhuber/eos
• Probabilistic Fitting: https://github.com/unibas-gravis/scalismo-faces
• Deep Neural Network parameter regression: https://talhassner.github.io/home/publication/2017_CVPR
• Expression-Net: https://github.com/fengju514/Expression-Net
• Face-Pose-Net: https://github.com/fengju514/Face-Pose-Net
• Shape-Net: https://github.com/anhttran/3dmm_cnn
• Extreme 3D Face Reconstruction: https://github.com/anhttran/extreme_3d_faces
• FLAME fitting: Chumpy-based framework, Tensorflow-based framework
• 3D face shape and expression regression network (RingNet): https://github.com/soubhiksanyal/RingNet
• Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network https://github.com/YadiraF/PRNet
• Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation https://github.com/matansel/pix2vertex
• 3D Morphable Models as Spatial Transformer Networks https://github.com/anilbas/3DMMasSTN
• Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric Regression https://github.com/AaronJackson/vrn
• Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set https://github.com/microsoft/Deep3DFaceReconstruction
• Facial Detail synthesis https://github.com/apchenstu/Facial_Details_Synthesis

Tutorials:

Web services: