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Tilman Wekel
Tilman Wekel
Director of Engineering, NVIDIA
Verified email at cs.stanford.edu
Title
Cited by
Cited by
Year
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
1042016
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
482022
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
392024
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
322024
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
172022
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
112008
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
82024
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
82021
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
42024
Selection of an optimal polyhedral surface model using the minimum description length principle
T Wekel, O Hellwich
Joint Pattern Recognition Symposium, 553-562, 2010
42010
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
32024
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
32022
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
32011
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
22008
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
12024
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
12015
Voronoi-based extraction of a feature skeleton from noisy triangulated surfaces
T Wekel, O Hellwich
Asian Conference on Computer Vision, 108-119, 2012
12012
Automatic propagation of labels between sensor representations for autonomous systems and applications
A Mitrokhin, R Parys, A Solovey, T Wekel
US Patent App. 18/305,185, 2024
2024
Generating maps representing dynamic objects for autonomous systems and applications
A Mitrokhin, R Parys, A Solovey, T Wekel
US Patent App. 18/305,153, 2024
2024
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
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