Christian Benz

Christian Benz is a member of the faculty of media at Bauhaus-University since 2019. He studied computer science at TU Darmstadt (B. Sc. and M. Sc.) and specialized in machine learning on image data. Parallel to completing his doctoral thesis in the field of crack detection, he has been working part-time as a Computer Vision Scientist at ZEISS since fall 2023.

Selected Publications:

• Benz, C., & Rodehorst, V. (2024). OmniCrack30k: A Benchmark for Crack Segmentation and the Reasonable Effectiveness of Transfer Learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. [Paper]
  
  
• Benz, C., & Rodehorst, V. (2024). ENSTRECT: A Stage-based Approach to 2.5D Structural Damage Detection. In European Conference on Computer Vision (ECCV) Workshops. Cham: Springer. (Accepted manuscript) [Preprint]
  
  
• Benz, C., & Rodehorst, V. (2024). MVCrackViT: Robust Multi-View Crack Detection for Point Cloud Segmentation using View Attention. In International Conference on Image Processing (ICIP). IEEE. (Accepted manuscript)
  
  
• Flotzinger, J., Rösch, P. J., Benz, C., Ahmad, M., Cankaya, M., Mayer, H., ... & Braml, T. (2024). dacl-challenge: Semantic Segmentation during Visual Bridge Inspections. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops. [Paper]
  
  
• Benz, C., & Rodehorst, V. (2022). Image-based Detection of Structural Defects using Hierarchical Multi-Scale Attention. In DAGM German Conference on Pattern Recognition (GCPR). Springer, Cham. [Paper]
  
  
• Benz, C., & Rodehorst, V. (2021). Model-based Crack Width Estimation using Rectangle Transform. In 2021 17th International Conference on Machine Vision and Applications (MVA). IEEE. [Paper]
  
  
• Benz, C., Debus, P., Ha, H.-K., & Rodehorst, V. (2019). Crack Segmentation on UAS-based Imagery using Transfer Learning. Angenommen für Image and Vision Computing New Zealand (IVCNZ). [Paper]