| Generic 3d representation via pose estimation and matching AR Zamir, T Wekel, P Agrawal, C Wei, J Malik, S Savarese Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 104 | 2016 |
| Multi-view deep neural network for LiDAR perception N Smolyanskiy, R Oldja, K Chen, A Popov, J Pehserl, I Eden, T Wekel, ... US Patent 11,532,168, 2022 | 44 | 2022 |
| Object detection and classification using LiDAR range images for autonomous machine applications T Wekel, S Oh, D Nister, J Pehserl, N Cvijetic, I Eden US Patent 11,906,660, 2024 | 35 | 2024 |
| Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications K Chen, N Smolyanskiy, A Kamenev, R Oldja, T Wekel, D Nister, ... US Patent 12,051,206, 2024 | 30 | 2024 |
| Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications A Popov, N Smolyanskiy, R Oldja, S Murray, T Wekel, D Nister, J Pehserl, ... US Patent 11,531,088, 2022 | 17 | 2022 |
| Vision based obstacle detection for wheeled robots T Wekel, O Kroll-Peters, S Albayrak 2008 International Conference on Control, Automation and Systems, 1587-1592, 2008 | 11 | 2008 |
| Top-down object detection from lidar point clouds N Smolyanskiy, R Oldja, K Chen, A Popov, J Pehserl, I Eden, T Wekel, ... US Patent App. 17/377,064, 2021 | 8 | 2021 |
| Multi-view deep neural network for LiDAR perception N Smolyanskiy, R Oldja, K Chen, A Popov, J Pehserl, I Eden, T Wekel, ... US Patent 12,080,078, 2024 | 7 | 2024 |
| Segmentation of lidar range images N Smolyanskiy, R Oldja, K Chen, A Popov, J Pehserl, I Eden, T Wekel, ... US Patent 12,072,443, 2024 | 4 | 2024 |
| Selection of an optimal polyhedral surface model using the minimum description length principle T Wekel, O Hellwich Joint Pattern Recognition Symposium, 553-562, 2010 | 4 | 2010 |
| Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications A Popov, N Smolyanskiy, R Oldja, S Murray, T Wekel, D Nister, J Pehserl, ... US Patent 11,960,026, 2024 | 3 | 2024 |
| Ground truth data generation for deep neural network perception in autonomous driving applications T Wekel, J Pehserl, J Meyer, J Guza, A Mitrokhin, R Whitcomb, M Scoffier, ... US Patent App. 17/187,350, 2022 | 3 | 2022 |
| Monocular rectangle reconstruction-based on direct linear transformation C Wefelscheid, T Wekel, O Hellwich International Conference on Computer Vision Theory and Applications 2, 271-276, 2011 | 3 | 2011 |
| Mono vision based construction of elevation maps in indoor environments T Wekel, O Kroll-Peters, C Wefelscheid, S Albayrak Proceedings of the 8th conference on Signal processing, computational …, 2008 | 2 | 2008 |
| Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications A Popov, N Smolyanskiy, R Oldja, S Murray, T Wekel, D Nister, J Pehserl, ... US Patent 11,885,907, 2024 | 1 | 2024 |
| Semantic segmentation and model fitting for triangulated surfaces using random jumps and graph cuts T Wekel, O Hellwich International Conference on Computer Vision Theory and Applications 2, 241-250, 2015 | 1 | 2015 |
| Voronoi-based extraction of a feature skeleton from noisy triangulated surfaces T Wekel, O Hellwich Asian Conference on Computer Vision, 108-119, 2012 | 1 | 2012 |
| Multi-view deep neural network for lidar perception N Smolyanskiy, R Oldja, K Chen, A Popov, J Pehserl, I Eden, T Wekel, ... US Patent App. 18/647,415, 2024 | | 2024 |
| Object detection and classification using lidar range images for autonomous machine applications T Wekel, S Oh, D Nister, J Pehserl, N Cvijetic, I Eden US Patent App. 18/531,103, 2024 | | 2024 |
| Freespace detection using machine learning for autonomous systems and applications A Popov, D Nister, N Smolyanskiy, P Gebhardt, K Chen, R Oldja, HS Lee, ... US Patent App. 18/366,298, 2024 | | 2024 |
