This repository contains code for the paper "Learning 3D Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton Formats" by István Sárándi, Alexander Hermans, and Bastian Leibe. The paper relies also on code from several other repos, including metrabs and posepile. This repo is specifically for the ACAE part.

See the train_acae function in acae.py for how to train an ACAE.

If you find this code useful, consider citing the paper:

@inproceedings{Sarandi2023acae,
    author = {S\'ar\'andi, Istv\'an and Hermans, Alexander and Leibe, Bastian},
    title = {Learning {3D} Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton Formats},
    booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
    year = {2023}
} 

GNU Affero General Public License, Version 3 (AGPL-3.0)

This software is a research prototype only and shall only be used for test-purposes. This software must not be used in or for products and/or services and in particular not in or for safety-relevant areas. It was solely developed for and published as part of the publication ‘Learning 3D Human Pose Estimation From Dozens of Datasets Using a Geometry-Aware Autoencoder To Bridge Between Skeleton Formats’ and will neither be maintained nor monitored in any way.