This code is a toolbox that uses PyTorch for training and evaluating the ERFNet architecture for semantic segmentation.
[NEWS] We have limited the code visibility for commercial reasons. If you need the code for research please contact me at eduardo.romera (at) edu.uah.es. Sorry for the inconvenience!
If you use this software in your research, please cite our publications:
"Efficient ConvNet for Real-time Semantic Segmentation", E. Romera, J. M. Alvarez, L. M. Bergasa and R. Arroyo, IEEE Intelligent Vehicles Symposium (IV), pp. 1789-1794, Redondo Beach (California, USA), June 2017. [Best Student Paper Award], [pdf]
"ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation", E. Romera, J. M. Alvarez, L. M. Bergasa and R. Arroyo, Transactions on Intelligent Transportation Systems (T-ITS), December 2017. [pdf]
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which allows for personal and research use only. For a commercial license please contact the authors. You can view a license summary here: http://creativecommons.org/licenses/by-nc/4.0/