@CONFERENCE{MTMT:34504666,
	title = {Radiation Plan Optimization for UV-C Disinfection Robots},
	url = {https://m2.mtmt.hu/api/publication/34504666},
	author = {Bugár-Mészáros, Barnabás and Majdik, András and Rózsa, Zoltán and Szirányi, Tamás},
	booktitle = {Proceedings of KEPAF 2023: Képfeldolgozók és Alakfelismerők társaságának 14. konferenciája},
	unique-id = {34504666},
	year = {2023},
	pages = {1-4},
	orcid-numbers = {Majdik, András/0000-0003-1807-2865; Szirányi, Tamás/0000-0003-2989-0214}
}

@CONFERENCE{MTMT:34504606,
	title = {LIDAR mérések időbeli felskálázása mono kamera alapján},
	url = {https://m2.mtmt.hu/api/publication/34504606},
	author = {Rózsa, Zoltán and Szirányi, Tamás},
	booktitle = {Proceedings of KEPAF 2023: Képfeldolgozók és Alakfelismerők társaságának 14. konferenciája},
	unique-id = {34504606},
	year = {2023},
	pages = {1-13},
	orcid-numbers = {Szirányi, Tamás/0000-0003-2989-0214}
}

@article{MTMT:33822096,
	title = {Optical Flow and Expansion Based Deep Temporal Up-Sampling of LIDAR Point Clouds},
	url = {https://m2.mtmt.hu/api/publication/33822096},
	author = {Rózsa, Zoltán and Szirányi, Tamás},
	doi = {10.3390/rs15102487},
	journal-iso = {REMOTE SENS-BASEL},
	journal = {REMOTE SENSING},
	volume = {15},
	unique-id = {33822096},
	abstract = {This paper proposes a framework that enables the online generation of virtual point clouds relying only on previous camera and point clouds and current camera measurements. The continuous usage of the pipeline generating virtual LIDAR measurements makes the temporal up-sampling of point clouds possible. The only requirement of the system is a camera with a higher frame rate than the LIDAR equipped to the same vehicle, which is usually provided. The pipeline first utilizes optical flow estimations from the available camera frames. Next, optical expansion is used to upgrade it to 3D scene flow. Following that, ground plane fitting is made on the previous LIDAR point cloud. Finally, the estimated scene flow is applied to the previously measured object points to generate the new point cloud. The framework’s efficiency is proved as state-of-the-art performance is achieved on the KITTI dataset.},
	year = {2023},
	eissn = {2072-4292},
	orcid-numbers = {Szirányi, Tamás/0000-0003-2989-0214}
}

@inproceedings{MTMT:33592095,
	title = {Környező járművek mozgásának meghatározása irány becslésre és kép-párok közötti epipoláris geometriára építve},
	url = {https://m2.mtmt.hu/api/publication/33592095},
	author = {Golarits, Marcell and Rózsa, Zoltán and Szirányi, Tamás},
	booktitle = {X. Magyar Számítógépes Grafika és Geometria Konferencia},
	unique-id = {33592095},
	year = {2022},
	pages = {122-127},
	orcid-numbers = {Golarits, Marcell/0000-0001-9652-4148; Szirányi, Tamás/0000-0003-2989-0214}
}

@article{MTMT:33078836,
	title = {Immediate Vehicle Movement Estimation and 3D Reconstruction for Mono Cameras by Utilizing Epipolar Geometry and Direction Prior},
	url = {https://m2.mtmt.hu/api/publication/33078836},
	author = {Rózsa, Zoltán and Golarits, Marcell and Szirányi, Tamás},
	doi = {10.1109/TITS.2022.3199046},
	journal-iso = {IEEE T INTELL TRANSP},
	journal = {IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS},
	volume = {23},
	unique-id = {33078836},
	issn = {1524-9050},
	year = {2022},
	eissn = {1558-0016},
	pages = {23548-23558},
	orcid-numbers = {Golarits, Marcell/0000-0001-9652-4148; Szirányi, Tamás/0000-0003-2989-0214}
}

@article{MTMT:32850291,
	title = {Temporal Up-Sampling of LIDAR Measurements Based on a Mono Camera},
	url = {https://m2.mtmt.hu/api/publication/32850291},
	author = {Rózsa, Zoltán and Szirányi, Tamás},
	doi = {10.1007/978-3-031-06430-2_5},
	journal-iso = {LNCS},
	journal = {LECTURE NOTES IN COMPUTER SCIENCE},
	volume = {13232},
	unique-id = {32850291},
	issn = {0302-9743},
	abstract = {Most of the 3D LIDAR sensors used in autonomous driving have significantly lower frame rates than modern cameras equipped to the same vehicle. This paper proposes a solution to virtually increase the frame rate of the LIDARs utilizing a mono camera, making possible the monitoring of dynamic objects with fast movement in the environment. First, dynamic object candidates are detected and tracked in the camera frames. Next, LIDAR points corresponding to these objects are identified. Then, virtual camera poses can be calculated by back projecting these points to the camera and tracking them. Finally, from the virtual camera poses, the object movement (transformation matrix transforming the object between frames) can be calculated (knowing the real camera poses) to the time moment, which does not have a corresponding LIDAR measurement. Static objects (rigid with the scene) can also be transformed to this time movement if the real camera poses are known. The proposed method has been tested in the Argoverse dataset, and it has outperformed earlier methods with a similar purpose.},
	keywords = {Computer Science, Information Systems; Computer Science, Artificial Intelligence; 3D geometry; LIDAR-camera fusion},
	year = {2022},
	eissn = {1611-3349},
	pages = {51-64},
	orcid-numbers = {Szirányi, Tamás/0000-0003-2989-0214}
}

@article{MTMT:32122541,
	title = {Positioning and perception in LIDAR point clouds},
	url = {https://m2.mtmt.hu/api/publication/32122541},
	author = {Benedek, Csaba and Majdik, András and Nagy, Balázs and Rózsa, Zoltán and Szirányi, Tamás},
	doi = {10.1016/j.dsp.2021.103193},
	journal-iso = {DIGIT SIGNAL PROCESS},
	journal = {DIGITAL SIGNAL PROCESSING},
	volume = {119},
	unique-id = {32122541},
	issn = {1051-2004},
	year = {2021},
	eissn = {1095-4333},
	orcid-numbers = {Benedek, Csaba/0000-0003-3203-0741; Majdik, András/0000-0003-1807-2865; Szirányi, Tamás/0000-0003-2989-0214}
}

@inproceedings{MTMT:32029863,
	title = {Mono Camera Based Pallet Detection and Pose Estimation for Automated Guided Vehicles},
	url = {https://m2.mtmt.hu/api/publication/32029863},
	author = {Bohács, Gábor and Rózsa, Zoltán and Bertalan, Balint},
	booktitle = {LISS 2020},
	doi = {10.1007/978-981-33-4359-7_1},
	unique-id = {32029863},
	year = {2021},
	pages = {1-11}
}

@inproceedings{MTMT:32016263,
	title = {Water Hazard Depth Estimation for Safe Navigation of Intelligent Vehicles},
	url = {https://m2.mtmt.hu/api/publication/32016263},
	author = {Rózsa, Zoltán and Golarits, Marcell and Szirányi, Tamás},
	booktitle = {Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems},
	doi = {10.5220/0010438100900099},
	unique-id = {32016263},
	year = {2021},
	pages = {90-99},
	orcid-numbers = {Golarits, Marcell/0000-0001-9652-4148; Szirányi, Tamás/0000-0003-2989-0214}
}

@article{MTMT:31207094,
	title = {Localization of Map Changes by Exploiting SLAM Residuals},
	url = {https://m2.mtmt.hu/api/publication/31207094},
	author = {Rózsa, Zoltán and Golarits, Marcell and Szirányi, Tamás},
	doi = {10.1007/978-3-030-40605-9_27},
	journal-iso = {LNCS},
	journal = {LECTURE NOTES IN COMPUTER SCIENCE},
	volume = {12002},
	unique-id = {31207094},
	issn = {0302-9743},
	year = {2020},
	eissn = {1611-3349},
	pages = {312-324},
	orcid-numbers = {Rózsa, Zoltán/0000-0002-3699-6669; Golarits, Marcell/0000-0001-9652-4148; Szirányi, Tamás/0000-0003-2989-0214}
}