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Simple and Effective Approaches for Uncertainty Prediction in Facial Action Unit Intensity Regression

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UncertaintyRegression

The code for "Simple and Effective Approaches for Uncertainty Prediction in Facial Action Unit Intensity Regression" at FG 2020

All building blocks are part of this repository:

Installation

git clone [email protected]:twoertwein/UncertaintyRegression.git
cd UncertaintyRegression
poetry update
poetry run pip install torchvision --extra-index-url https://download.pytorch.org/whl/cu116

Usage

Run the grid-search for a primary model to predict facial action units (AU) intensities. Some primary models can also estimate their uncertainty.

python train.py --method dropout --workers 4 --dataset mnist

Train a secondary model to estimate the uncertainty of the primary dropout model.

python train_secundary.py --uncertainty umlp --workers 4 --dataset mnist

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Simple and Effective Approaches for Uncertainty Prediction in Facial Action Unit Intensity Regression

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