(ACMMM 2021 Oral) SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment

This repository shows two tasks: Face landmark detection and Face 3D reconstruction, which is described in this paper: Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

Installation

1. Clone the repository.
2. install dependencies.

pip install -r requirement.txt

Face landmark detection

Running a pre-trained model

1. Download landmark pre-trained model at GoogleDrive, and put it into FaceLandmark/model/
2. Run the test file

python Facial_landmark.py

Face 3D reconstruction

Running a pre-trained model

1. Download face 3D reconstruction pre-trained model at GoogleDrive, and put it into FaceReconstruction/checkpoints/

2. Run the inference.py file to generate disparity map

python inference.py --dataset-dir './FaceReconstruction/test_image/' --output-dir './FaceReconstruction/output/' --pretrained './FaceReconstruction/checkpoints/dispnet_model_best.pth.tar' --resnet-layers 18 --output-disp 

4. Run the generate_ply.py file to generate point cloud .ply file

python generate_ply.py