PyTorch implementation of "Super-Realtime Facial Landmark Detection and Shape Fitting by Deep Regression of Shape Model Parameters" predicting facial landmarks with up to 400 FPS
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Updated
May 24, 2020 - Python
PyTorch implementation of "Super-Realtime Facial Landmark Detection and Shape Fitting by Deep Regression of Shape Model Parameters" predicting facial landmarks with up to 400 FPS
Facial landmarks detection with OpenCV, Dlib, DNN
Real-time selfie filters using facial keypoints regression and opencv
Facial Landmark Detection using OpenCV and Mediapipe
This repository contains my implementation of a shape-constrained network which predicts up to 170 FPS
a computer vision project to recognize facial keypoints
Detect different parts of the face such as, eyes brows, nose, jaw, etc. individually
Use a webcam as a mirror to view your NYC/FB data identities
Using dlib, OpenCV, and Python, to detect in real time how to open/closed eyes,mouth, position of the head, and the emotion
Facial keypoints detection using Haar Cascade and CNN.
Facial-Keypoints detection in Real time
Detecting Facial Keypoints (Landmarks) using a custom CNN architecture
Facial keypoints detection using Pytorch
Upon sleep detection, the code will trigger notifications that include a combination of gentle vibrations on the watch and an escalating audio alert on the phone. This approach provides a multi-sensory wake-up cue to increase the user's chance of being roused from sleep.
Detect facial landmarks using OpenCV, dlib, Python
A toy module to play with facial filters using face alignment models and some geometry.
Think about boundary: Fusing multi-level boundary information for landmark heatmap regression.
Implementation and Training of a CNN for Facial Keypoints Detection
Real-time Monitoring System using Computer Vision
Facial Landmark detector - eyes, nose, mouth (CPU compute optimised, IoT capable)
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