Implementation of PFLD A Practical Facial Landmark Detector , reference to https://arxiv.org/pdf/1902.10859.pdf
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Updated
Feb 2, 2023 - Python
Implementation of PFLD A Practical Facial Landmark Detector , reference to https://arxiv.org/pdf/1902.10859.pdf
A 3D Slicer extension to use AMASSS, ALI-CBCT and ALI-IOS
Code for BMVC2021 "MOS: A Low Latency and Lightweight Framework for Face Detection, Landmark Localization, and Head Pose Estimation"
Face alignment tool for transforming face images into FFHQ-style.
SourceCode of serial tutorials on 3D Slicer extension development for beginners
Train-Predict-Landmarks-by-flat
PyTorch-based toolkit for landmark localization
This Module is designed for spine deformity analysis using freehand 3D ultrasound imaging, and the first module Lamina Landmark Labeling help find the Spinal Cord curve in 3D, which can be projected to three anatomical planes, e.g., for Scoliosis analysis using the Cobb angle when projected to the front back view.
Train Predict Landmarks by dlib
Landmark detection by shapenet
Train-Predict-Landmarks-by-RCN
Face alignment tool for transforming face images into FFHQ-style.
Train-Predict-Landmarks-by-Autoencoder
'Mobile Robotics' Assignment #12: Localization by Landmarks
Code from TMI paper "Deep learning-based regression and classification for automatic landmark localization in medical images".
Train Predict Landmarks by Deep Alignment Network (DAN)
Train Predict Landmarks by Multi-context attention
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