Facial Landmark Detection and head pose compute use dlib, Real time Face Reconstruction use 3D Morphable Face Model fitting

A demo for face reconstruction using kinect.

Face Reconstruction In The Wild

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code used on the paper Face Reconstruction with Variational Autoencoder and Face Masks https://arxiv.org/abs/2112.02139

A Qt project which build a face mesh with olny one picture

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C++ Real-time 3D face reconstruction project from a single RGB-D image

3D Reconstruction of human faces from still images

3D-FaceReconstruction is a Python-based pipeline that reconstructs high-quality 3D facial meshes from a single 2D image. It integrates facial landmark detection, mesh generation, texture mapping, and depth estimation, making it ideal for applications in AR/VR, gaming, and digital avatars.

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Facial reconstruction with recorded Kinect data on MacOS

For Multimedia 805

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Implementation of EMICA for 3D face reconstruction (a combination of DECA, EMOCA, SPECTRE and MICA).

人脸建模

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Uses Principal Component Analysis to find inroads into the computer vision problem of facial recognition. PCA is used to reduce data variables by extracting important features from a large dataset. PCA code is written from the ground up. This reduces the feature set from 5655 entries to 2. It is seen that a face can be reconstructed with 95% accuracy using only 180 features as compared to the 5655 features intially provided. This saves a lot computation time and space, while still being an accurate model for face recognition.

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Colabs to run and test out the current face reconstruction algorithms