Official implementation of our research on stop-and-go wave super-resolution reconstruction via iterative refinement.
Note: This release includes only the code for the conditional diffusion model presented in the paper.
@article{ji2025wavex,
title = {Stop-and-go wave super-resolution reconstruction via iterative refinement},
journal = {Transportation Research Part C: Emerging Technologies},
volume = {180},
pages = {105313},
year = {2025},
issn = {0968-090X},
doi = {https://doi.org/10.1016/j.trc.2025.105313},
url = {https://www.sciencedirect.com/science/article/pii/S0968090X25003171},
author = {Junyi Ji and Alex Richardson and Derek Gloudemans and Gergely Zachár and Matthew Nice and William Barbour and Jonathan Sprinkle and Benedetto Piccoli and Daniel B. Work},
keywords = {Stop-and-go waves, Super resolution, Generative artificial intelligence, Diffusion model}
}
We are benefiting from the following Github projects: