Accepted at CHI 2026 (ACM Conference on Human Factors in Computing Systems)
Inês Cardoso Oliveira, Sena Kilinç, Luis A. Leiva
AutoChainer is an automatic DA technique suitable for stroke-based data, that consists of applying random chains of augmentation transformations.
This method improves recognition performance while maintaining visual fidelity and offering flexible customization.
Code release coming soon. This repository is currently being prepared.
@inproceedings{10.1145/3772318.3791836,
author = {Cardoso Oliveira, In\^{e}s and Kilin\c{c}, Sena and Leiva, Luis A.},
title = {AutoChainer: Automatic Data Augmentation for Stroke-based Input},
year = {2026},
isbn = {9798400722783},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3772318.3791836},
doi = {10.1145/3772318.3791836},
booktitle = {Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems},
series = {CHI '26}
}