Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

Last update: Dec 13, 2022

Overview

(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

Clone the repository.
install dependencies.

pip install -r requirement.txt

Face landmark detection

Running a pre-trained model

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

python Facial_landmark.py

Face 3D reconstruction

Running a pre-trained model

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

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

python generate_ply.py

Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

Related tags

Overview

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

Installation

Face landmark detection

Running a pre-trained model

Face 3D reconstruction

Running a pre-trained model

Owner

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