The repository contains the related code for the paper, "Hyperbolic Uncertainty Aware Semantic Segmentation".
The SegFormer-B0 is used as the semantic image segmentation model. Besides, I do not intend to provide the whole code, because previous models cannot achieve optimal performance due to the lack of various data augmentation techniques.
However, I plan to submit the newly developed semantic image segmentation code to the other repository. Also, I will paste the link here.
If you have any questions, please drop me an email, "[email protected]". Please note that you email might be filtered as the trash email, and then I may not reply to you immediately.
[1] https://github.com/leymir/hyperbolic-image-embeddings
[2] https://github.com/geoopt/geoopt
@article{hyperul2024,
author={Chen, Bike and Peng, Wei and Cao, Xiaofeng and Röning, Juha},
journal={IEEE Transactions on Intelligent Transportation Systems},
title={Hyperbolic Uncertainty Aware Semantic Segmentation},
year={2024},
volume={25},
number={2},
pages={1275-1290},
keywords={Uncertainty;Training;Estimation;Computational modeling;Semantic segmentation;Drones;Task analysis;Hyperbolic space;hyperbolic uncertainty estimation;semantic segmentation;self-driving cars;autonomous drones},
doi={10.1109/TITS.2023.3312290}}