| On deep learning-based channel decoding T Gruber, S Cammerer, J Hoydis, S ten Brink 2017 51st Annual Conference on Information Sciences and Systems (CISS), 1-6, 2017 | 598 | 2017 |
| Seeing through fog without seeing fog: Deep multimodal sensor fusion in unseen adverse weather M Bijelic, T Gruber, F Mannan, F Kraus, W Ritter, K Dietmayer, F Heide Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 455* | 2020 |
| Scaling deep learning-based decoding of polar codes via partitioning S Cammerer, T Gruber, J Hoydis, S ten Brink GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-6, 2017 | 243 | 2017 |
| A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down? M Bijelic, T Gruber, W Ritter 2018 IEEE Intelligent Vehicles Symposium (IV), 760-767, 2018 | 203 | 2018 |
| Benchmarking Image Sensors Under Adverse Weather Conditions for Autonomous Driving M Bijelic, T Gruber, W Ritter 2018 IEEE Intelligent Vehicles Symposium (IV), 1773-1779, 2018 | 81 | 2018 |
| Gated2depth: Real-time dense lidar from gated images T Gruber, F Julca-Aguilar, M Bijelic, F Heide Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 68 | 2019 |
| Pixel-Accurate Depth Evaluation in Realistic Driving Scenarios T Gruber, M Bijelic, F Heide, W Ritter, K Dietmayer 2019 International Conference on 3D Vision (3DV), 95-105, 2019 | 34 | 2019 |
| Uncertainty depth estimation with gated images for 3D reconstruction S Walz, T Gruber, W Ritter, K Dietmayer 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 16 | 2020 |
| Benchmarking Automotive LiDAR Performance in Arctic Conditions M Kutila, P Pyykönen, M Jokela, T Gruber, M Bijelic, W Ritter 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 14 | 2020 |
| Recovering the Unseen: Benchmarking the Generalization of Enhancement Methods to Real World Data in Heavy Fog. M Bijelic, P Kysela, T Gruber, W Ritter, K Dietmayer CVPR Workshops, 11-21, 2019 | 14 | 2019 |
| Learning Super-resolved Depth from Active Gated Imaging T Gruber, M Kokhova, W Ritter, N Haala, K Dictmayer 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 13 | 2018 |
| DENSE: environment perception in bad weather—First results W Ritter, M Bijelic, T Gruber, M Kutila, H Holzhüter Electronic Components and Systems for Automotive Applications: Proceedings …, 2019 | 10 | 2019 |
| Gated Imaging for Autonomous Driving in Adverse Weather T Gruber, M Bijelic, W Ritter, K Dietmayer, AG Daimler CVPR'19 Workshop Vision for All Seasons: Bad Weather and Nighttime, 2019 | 5 | 2019 |
| High-Resolution Gated Depth Estimation for Self-Driving Cars in AdverseWeather T Gruber, S Walz, W Ritter, K Dietmayer Automatisiertes Fahren 2020: Von der Fahrerassistenz zum autonomen Fahren 6 …, 2021 | | 2021 |
| Real-time super-resolved depth estimation for self-driving cars from multiple gated images T Gruber Universität Ulm, 2020 | | 2020 |
| Automotive Sensor Performance in Adverse Weather M Bijelic, T Gruber, W Ritter, K Dietmayer, AG Daimler | | |
Mario BijelicPrinceton University在 princeton.edu 的电子邮件经过验证
