Deep Fusion of Camera and LIDAR
Fusing camera and LIDAR data in autonomous driving poses challenges such as accurate calibration, differing data representations, and extensive training data requirements. This dissertation addresses these by three contributions: a deep neural network for LIDAR-to-camera calibration, two depth compl...
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| Format: | Online |
| Idioma: | anglès |
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KIT Scientific Publishing
2026
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| Accés en línia: | 1613-4214 (Online) |
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| _version_ | 1869514629898567680 |
|---|---|
| author | Schneider, Nick |
| author_browse | Schneider, Nick |
| author_facet | Schneider, Nick |
| author_sort | Schneider, Nick |
| collection | Directory of Open Access Books |
| description | Fusing camera and LIDAR data in autonomous driving poses challenges such as accurate calibration, differing data representations, and extensive training data requirements. This dissertation addresses these by three contributions: a deep neural network for LIDAR-to-camera calibration, two depth completion approaches for processing sparse depth measurements in the image space, and a large-scale dataset of 93k RGB and depth images for training and evaluating deep networks. |
| format | Online |
| id | doab-20.500.12854ir-173626 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | KIT Scientific Publishing |
| publisherStr | KIT Scientific Publishing |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1736262026-03-19T13:26:15Z Deep Fusion of Camera and LIDAR Schneider, Nick Bildverstehen Computer Vision Machine Learning Neural Networks Neuronale Netze Sensor Fusion Sensorfusion Maschinelles Lemen thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGB Mechanical engineering Fusing camera and LIDAR data in autonomous driving poses challenges such as accurate calibration, differing data representations, and extensive training data requirements. This dissertation addresses these by three contributions: a deep neural network for LIDAR-to-camera calibration, two depth completion approaches for processing sparse depth measurements in the image space, and a large-scale dataset of 93k RGB and depth images for training and evaluating deep networks. 2026-03-19T13:26:14Z 2026-03-19T13:26:14Z 2026-03-17T16:48:21Z 2026 book 1613-4214 (Online) https://library.oapen.org/handle/20.500.12657/112078 9783731513612 9783731513261 https://directory.doabooks.org/handle/20.500.12854/173626 eng Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/112078/1/9783731513612.pdf KIT Scientific Publishing KIT Scientific Publishing 10.5445/KSP/1000169933 10.5445/KSP/1000169933 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731513612 9783731513261 KIT Scientific Publishing 140 Karlsruhe, Germany open access |
| spellingShingle | Bildverstehen Computer Vision Machine Learning Neural Networks Neuronale Netze Sensor Fusion Sensorfusion Maschinelles Lemen thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGB Mechanical engineering Schneider, Nick Deep Fusion of Camera and LIDAR |
| title | Deep Fusion of Camera and LIDAR |
| title_full | Deep Fusion of Camera and LIDAR |
| title_fullStr | Deep Fusion of Camera and LIDAR |
| title_full_unstemmed | Deep Fusion of Camera and LIDAR |
| title_short | Deep Fusion of Camera and LIDAR |
| title_sort | deep fusion of camera and lidar |
| topic | Bildverstehen Computer Vision Machine Learning Neural Networks Neuronale Netze Sensor Fusion Sensorfusion Maschinelles Lemen thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGB Mechanical engineering |
| topic_facet | Bildverstehen Computer Vision Machine Learning Neural Networks Neuronale Netze Sensor Fusion Sensorfusion Maschinelles Lemen thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGB Mechanical engineering |
| url | 1613-4214 (Online) |
| work_keys_str_mv | AT schneidernick deepfusionofcameraandlidar |