Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders"

Last update: Dec 01, 2022

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Overview

DECA

Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders". All the code is written using Pytorch Lightning. Please use Pipenv to configure the virtual environment required to run the code.

How to run

Use the following command to configure the virtual environment:

pipenv install

To configure all the network parameters, including the dataset paths and hyperparameters, please edit the file:

config/config_TV.cfg

or add each parameter as a runtime flag while executing the main.py file as follows:

python main.py --flagfile config/config_TV.cfg

As an example, to run the network in training mode with a dataset stored in , you can run the following command:

python main.py --flagfile config/config_TV.cfg --mode train --dataset_dir <datasetpath>

Owner

GitHub Repository

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