About RAIL-BENCH
RAIL-BENCH is the first perception benchmark suite for the railway domain. Automated train operation requires robust camera-based perception, yet the railway domain lacks public benchmark suites with standardized evaluation protocols that would enable reproducible comparison of approaches. RAIL-BENCH addresses this gap by providing curated training and test datasets drawn from diverse real-world scenarios, evaluation metrics, and public leaderboards — spanning five distinct perception tasks:
News
- 02.06.2026 All RAIL-BENCH challenges are now open for submissions on the CodaBench platform. Just search for "RAIL-BENCH" and you will find all five challenges or look for the direct links on our individual challenge pages. We can't wait to see your submissions and how you tackle the unique challenges of railway perception!
- 24.04.2026 Our paper is on arXiv! Read about the motivation, design, and details of RAIL-BENCH in our preprint: View arXiv Preprint
- 16.04.2026 Our project presentation slides are now available! Learn how and why we built RAIL-BENCH, and why benchmark suites are essential for advancing perception in the railway domain: View Presentation Slides
Citation
If you use RAIL-BENCH in your research, please cite it as follows:
Baetz, A., Klasek, P., Ham, S.-Y., Neumaier, P., Koeppel, M., & Lauer, M. (2026). Railway Artificial Intelligence Learning Benchmark (RAIL-BENCH): A Benchmark Suite for Perception in the Railway Domain. arXiv preprint arXiv:2604.22507.
Terms of Use
By using RAIL-BENCH, you agree to:
- Use the datasets for research and non-commercial purposes only.
- Properly cite RAIL-BENCH in your work.
- Not redistribute or commercialize the content without permission.
Contact
For questions or inquiries, please reach out to: