ROADVIEW publications, pre-prints, and conference proceedings
2024
Cortinhal, T., & Aksoy, E. E. (2024). Depth- and semantics-aware multi-modal domain translation: Generating 3D panoramic color images from Lidar Point Clouds. Robotics and Autonomous Systems, 171, 104583. https://doi.org/10.1016/j.robot.2023.104583
Shahbeigi, S., Robinson, J., Donzella, V. (2024). A Novel Score-based LiDAR Cloud Degradation Analysis Method. IEEEAccess, 10.1109/ACCESS.2024.3359300
2023
Wang, Y., Zhao, H., Debattista, K. and Donzella, V. (2023). The effect of camera data degradation factors on panoptic segmentation for automated driving. WRAP, https://wrap.warwick.ac.uk/177340/
Duarte Silva, L. C., Funk Drechsler, M., Poledna, Y., Huber, W., & Fiorentin, A. (2023). Synthetic Extreme Weather for AI training: Concept and Validation. IEEExplore, 10.1109/DDP60485.2023.00044
Ben-Daoued, A., Duthon, P., & Bernardin, F. (2023). Sweet: A realistic multiwavelength 3D simulator for automotive perceptive sensors in foggy conditions. Journal of Imaging, 9 (2), 54. https://doi.org/10.3390/jimaging9020054
Chan, P. H., Wei, C., Huggett, A., & Donzella, V. (2023). Raw Camera Data Object Detectors: An Optimisation for Automotive Processing and Transmission. TechRxiv, https://doi.org/10.36227/techrxiv.23807499.v1
Baris, G., Li, B., Chan, P. H., Avizzano, C. A., & Donzella, V. (2023). Analysis of Faster R-CNN Network Prediction in the Presence of Lens Occlusion and Video Compression. TechRxiv, https://doi.org/10.36227/techrxiv.23047412.v1
Pesonen, J. (2023). Pixelwise Road Surface Slipperiness Estimation for Autonomous Driving with Weakly Supervised Learning. Altodoc Publication Archive, https://urn.fi/URN:NBN:fi:aalto-202310156442
Raisuddin, A. M., Cortinhal, T., Holmblad, J., & Aksoy, E. E. (2023). 3D-OutDet: A Fast and Memory Efficient Outlier Detector for 3D Lidar Point Clouds in Adverse Weather. TechRxiv, https://doi.org/10.36227/techrxiv.24297166.v1
Raisuddin, A. M., Cortinhal, T., Holmblad, J., & Aksoy, E. E. (2023). Supplementary Information: 3D-OutDet: A Fast and Memory Efficient Outlier Detector for 3D Lidar Point Clouds in Adverse Weather. TechRxiv. https://doi.org/10.36227/techrxiv.24297166.v1
Cortinhal, T., Gouigah, I., Aksoy, E. E. (2023) Semantics-aware LiDAR-Only Pseudo Point Cloud Generation for 3D Object Detection. ArXiv Cornell University, https://doi.org/10.48550/arXiv.2309.08932
Chan, P. H., Shahbeigi Roudposhti, S., Ye, X., & Donzella, V. (2023). A Noise Analysis of 4D Radar: Robust Sensing for Automotive?. TechRxiv https://doi.org/10.36227/techrxiv.24517249.v1
Gummadi, D., Chan, P. H., Wang, H., & Donzella, V. (2023). Correlating Traditional Image Quality Metrics and DNN-Based Object Detection: A Case Study with Compressed Camera Data. TechRxiv. https://doi.org/10.36227/techrxiv.24566371.v1
ROADVIEW datasets
Poledna, Y., Dreschler, M., Cristófoli Duarte, L., Duthon, P., Bernardin, F., Donzella, V., Chan, P. H. (2024). REHEARSE: adveRse wEatHEr datAset for sensoRy noiSe modEls. RISE. https://s3.ice.ri.se/roadview-WP3-Warwick/T3.2%20-%20Create%20Dataset/rehearse/index.html
Poledna, Y., Dreschler, M., Hjort, M., Kharrazi, S. (2024). Vehicle Dynamics. GitHub. https://github.com/roadview-project/vehicle-dynamics
Poledna, Y., (2024). Dataset Creator OSI. GitHub. https://github.com/roadview-project/dataset_creator_OSI
