The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.

Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision

This is a implementation of the 3D FLAME model in PyTorch

Automatic 3D Character animation using Pose Estimation and Landmark Generation techniques

A tool for precisely placing 3D landmarks on 3D facial scans based on the paper "Multi-view Consensus CNN for 3D Facial Landmark Placement"

This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.

Keras implementation of "Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues" paper

[ECCV 24 wksp] Pose-independent 3D Anthropometry from Sparse Data

This project extracts 3D face landmarks based on 2d screenshots of a 3D face (Lateral Left, Lateral Right and Front View)

3D landscape maps display program. Wrote on pure C using miniLibX.