LIDAR–camera fusion for road detection using fully convolutional neural networks
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Caltagirone et al. (2019) [129] achieve road segmentation performance on KITTI test set of MaxF 96.03%, AP 93.93%, PRE 96.23%, REC 95.83%, FPR 2.07%, FNR 4.17%.
“Caltagirone et al. , 2019 [129] | 96.03 % | 93.93 % | 96.23 % | 95.83 % | 2.07 % | 4.17 % | 0.15 s | GPU |”
From Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges (2021) · cites this paper as [129]
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Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946 · see citing works
Vision meets robotics: The KITTI dataset
Geiger, A., Lenz, P., Stiller, C., & Urtasun, R. (2013) · The International Journal of Robotics Research · doi:10.1177/0278364913491297 · Cited by 9,913 · see citing works
Multimodal vehicle detection: fusing 3D-LIDAR and color camera data
Asvadi, A., Garrote, L., Premebida, C., Peixoto, P., & J. Nunes, U. (2018) · Pattern Recognition Letters · doi:10.1016/j.patrec.2017.09.038 · Cited by 225 · see citing works
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Feng, D., Haase-Schutz, C., Rosenbaum, L., Hertlein, H., Glaser, C., Timm, F., Wiesbeck, W., & Dietmayer, K. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.2972974 · Cited by 1,425 · see citing works
Multi-Sensor Fusion in Automated Driving: A Survey
Wang, Z., Wu, Y., & Niu, Q. (2020) · IEEE Access · doi:10.1109/access.2019.2962554 · Cited by 526 · see citing works
Progressive LiDAR adaptation for road detection
Chen, Z., Zhang, J., & Tao, D. (2019) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2019.1911459 · Cited by 205 · see citing works
- Authors
- Caltagirone, L., Bellone, M., Svensson, L., & Wahde, M.
- Affiliations
- Chalmers University of Technology (SE)
- Corresponding author
- Caltagirone, Luca
- Venue
- Robotics and Autonomous Systems
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 111
- Pages
- 125-131
- ISSN
- 0921-8890 (ISSN-L)
- OpenAlex
- W2891529090
- Cited by
- 370
- References
- 3
- Citations by year
- 2026: 17 · 2025: 42 · 2024: 47 · 2023: 57 · 2022: 73 · 2021: 55 · 2020: 45 · 2019: 34
- FWCI
- 17.79
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Robotics and Autonomous Systems (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Chalmers Research (Chalmers University of Technology) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Vinnova/FFI, Sweden
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Engineering › Ocean Engineering › Automated Road and Building Extraction
- Keywords
- road detection, LiDAR-camera fusion, point cloud projection, point cloud upsampling, feature-level fusion, decision fusion, multimodal sensor fusion, fully convolutional network, autonomous driving perception
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