6DRepNet
taylor
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| 6DRepNet | taylor | |
|---|---|---|
| 4 | 4 | |
| 499 | 13 | |
| - | - | |
| 3.7 | 0.0 | |
| about 1 month ago | about 2 years ago | |
| Python | Python | |
| MIT License | - |
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6DRepNet
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How to do Human Head Segmentation from images?
Well so it sounds like you want to do something like DeepFaceLab? I don't have a lot of experience with that but I believe they collect facial images based on their angles (pitch, roll and yaw) and match and merge them together. So something like this might help you there: https://github.com/thohemp/6DRepNet
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Head Pose Estimation
I found this was the easiest one to get installed and up and running: https://github.com/thohemp/6DRepNet
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[R] 6D Rotation Representation For Unconstrained Head Pose
Code for https://arxiv.org/abs/2202.12555 found: https://github.com/thohemp/6DRepNet
taylor
What are some alternatives?
pytorch-geodesic-loss - A PyTorch criterion for computing the distance between rotation matrices.
DeepPoseKit - a toolkit for pose estimation using deep learning
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
misc - "For fun and profit"
pytorch-learn-reinforcement-learning - A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.
pycopent - Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python
Machine-Learning-Collection - A resource for learning about Machine learning & Deep Learning
PoseNDF - Implementation of Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fields
RSCalibration - Docs and scripts to estimate a camera's rolling shutter readout time
face-parsing.PyTorch - Using modified BiSeNet for face parsing in PyTorch
DAD-3DHeads - Official repo for DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image (CVPR 2022).