Keras implementation of Face recognition using triplet loss
-
Updated
Nov 3, 2020 - Jupyter Notebook
Keras implementation of Face recognition using triplet loss
Blender Add-on for the FLAME face model
The provided program loads a multilinear face model and fits this model to a point cloud or a triangle mesh.
A tool to blur faces or other regions in images and videos 🤡🔍
3D face modeling and recognition using a depth camera (RGBD)
Convert from Basel Face Model (BFM) to the FLAME head model
Build your own ArcFace, CenterFace/Centernet
Tensorflow framework for the FLAME 3D head model. The code demonstrates how to sample 3D heads from the model, fit the model to 2D or 3D keypoints, and how to generate textured head meshes from Images.
This is a implementation of the 3D FLAME model in PyTorch
Official repository accompanying a CVPR 2022 paper EMOCA: Emotion Driven Monocular Face Capture And Animation. EMOCA takes a single image of a face as input and produces a 3D reconstruction. EMOCA sets the new standard on reconstructing highly emotional images in-the-wild
Example code for the FLAME 3D head model. The code demonstrates how to sample 3D heads from the model, fit the model to 3D keypoints and 3D scans.
Add a description, image, and links to the face-model topic page so that developers can more easily learn about it.
To associate your repository with the face-model topic, visit your repo's landing page and select "manage topics."