@article{MTMT:34881244,
	title = {LidPose: Real-Time 3D Human Pose Estimation in Sparse Lidar Point Clouds with Non-Repetitive Circular Scanning Pattern},
	url = {https://m2.mtmt.hu/api/publication/34881244},
	author = {Kovács, Lóránt and Bódis, Balázs M. and Benedek, Csaba},
	doi = {10.3390/s24113427},
	journal-iso = {SENSORS-BASEL},
	journal = {SENSORS},
	volume = {24},
	unique-id = {34881244},
	abstract = {In this paper, we propose a novel, vision-transformer-based end-to-end pose estimation method, LidPose, for real-time human skeleton estimation in non-repetitive circular scanning (NRCS) lidar point clouds. Building on the ViTPose architecture, we introduce novel adaptations to address the unique properties of NRCS lidars, namely, the sparsity and unusual rosetta-like scanning pattern. The proposed method addresses a common issue of NRCS lidar-based perception, namely, the sparsity of the measurement, which needs balancing between the spatial and temporal resolution of the recorded data for efficient analysis of various phenomena. LidPose utilizes foreground and background segmentation techniques for the NRCS lidar sensor to select a region of interest (RoI), making LidPose a complete end-to-end approach to moving pedestrian detection and skeleton fitting from raw NRCS lidar measurement sequences captured by a static sensor for surveillance scenarios. To evaluate the method, we have created a novel, real-world, multi-modal dataset, containing camera images and lidar point clouds from a Livox Avia sensor, with annotated 2D and 3D human skeleton ground truth.},
	year = {2024},
	eissn = {1424-8220},
	pages = {3427},
	orcid-numbers = {Kovács, Lóránt/0000-0001-9930-348X; Bódis, Balázs M./0009-0001-1271-6386; Benedek, Csaba/0000-0003-3203-0741}
}

@CONFERENCE{MTMT:34693946,
	title = {Real-time foreground segmentation for surveillance applications in sequences from a Non-repetitive Circular Scanning Lidar},
	url = {https://m2.mtmt.hu/api/publication/34693946},
	author = {Kovács, Lóránt and Kégl, Marcell and Benedek, Csaba},
	booktitle = {Proceedings of KEPAF 2023: Képfeldolgozók és Alakfelismerők társaságának 14. konferenciája},
	unique-id = {34693946},
	year = {2023},
	orcid-numbers = {Kovács, Lóránt/0000-0001-9930-348X; Benedek, Csaba/0000-0003-3203-0741}
}

@CONFERENCE{MTMT:34693938,
	title = {Real-Time Surveillance Application for NRCS Lidar Sequences},
	url = {https://m2.mtmt.hu/api/publication/34693938},
	author = {Kégl, Marcell and Kovács, Lóránt and Benedek, Csaba},
	booktitle = {Proceedings of KEPAF 2023: Képfeldolgozók és Alakfelismerők társaságának 14. konferenciája},
	unique-id = {34693938},
	year = {2023},
	orcid-numbers = {Kovács, Lóránt/0000-0001-9930-348X; Benedek, Csaba/0000-0003-3203-0741}
}

@CONFERENCE{MTMT:34683873,
	title = {Abdominal aortic aneurysm segmentation and analysis from CTA images},
	url = {https://m2.mtmt.hu/api/publication/34683873},
	author = {Madaras, Vilmos and López-Linares Román, K and Benedek, Csaba},
	booktitle = {Proceedings of KEPAF 2023: Képfeldolgozók és Alakfelismerők társaságának 14. konferenciája},
	unique-id = {34683873},
	year = {2023},
	pages = {1-18},
	orcid-numbers = {Benedek, Csaba/0000-0003-3203-0741}
}

@article{MTMT:34106643,
	title = {Masonry Structure Analysis, Completion and Style Transfer Using a Deep Neural Network},
	url = {https://m2.mtmt.hu/api/publication/34106643},
	author = {Ibrahim, Yahya and Szulovszky, Péter and Benedek, Csaba},
	doi = {10.1007/978-3-031-37731-0_13},
	journal-iso = {LNCS},
	journal = {LECTURE NOTES IN COMPUTER SCIENCE},
	volume = {13645},
	unique-id = {34106643},
	issn = {0302-9743},
	year = {2023},
	eissn = {1611-3349},
	pages = {155-168},
	orcid-numbers = {Szulovszky, Péter/0000-0002-8792-9634; Benedek, Csaba/0000-0003-3203-0741}
}

@article{MTMT:33749450,
	title = {ST-DepthNet: A spatio-temporal deep network for depth completion using a single non-repetitive circular scanning Lidar},
	url = {https://m2.mtmt.hu/api/publication/33749450},
	author = {H. Zováthi, Örkény Ádám and Pálffy, Balázs and Jankó, Zsolt and Benedek, Csaba},
	doi = {10.1109/LRA.2023.3266670},
	journal-iso = {IEEE ROBOT AUTOM LETT},
	journal = {IEEE ROBOTICS AND AUTOMATION LETTERS},
	volume = {8},
	unique-id = {33749450},
	issn = {2377-3766},
	year = {2023},
	eissn = {2377-3766},
	pages = {3270-3277},
	orcid-numbers = {Jankó, Zsolt/0000-0002-3739-9874; Benedek, Csaba/0000-0003-3203-0741}
}

@article{MTMT:33745713,
	title = {MVPCC-Net: Multi-View Based Point Cloud Completion Network for MLS data},
	url = {https://m2.mtmt.hu/api/publication/33745713},
	author = {Ibrahim, Yahya and Benedek, Csaba},
	doi = {10.1016/j.imavis.2023.104675},
	journal-iso = {IMAGE VISION COMPUT},
	journal = {IMAGE AND VISION COMPUTING},
	volume = {134},
	unique-id = {33745713},
	issn = {0262-8856},
	year = {2023},
	eissn = {1872-8138},
	orcid-numbers = {Benedek, Csaba/0000-0003-3203-0741}
}

@inproceedings{MTMT:33288670,
	title = {Multi-view Based 3D Point Cloud Completion Algorithm for Vehicles},
	url = {https://m2.mtmt.hu/api/publication/33288670},
	author = {Ibrahim, Yahya and Nagy, Balázs and Benedek, Csaba},
	booktitle = {2022 26th International Conference on Pattern Recognition (ICPR)},
	doi = {10.1109/ICPR56361.2022.9956459},
	unique-id = {33288670},
	year = {2022},
	pages = {2121-2127},
	orcid-numbers = {Benedek, Csaba/0000-0003-3203-0741}
}

@inproceedings{MTMT:33240891,
	title = {Real-time Vehicle Localization and Pose Tracking in High-Resolution 3D Maps},
	url = {https://m2.mtmt.hu/api/publication/33240891},
	author = {H. Zováthi, Örkény Ádám and Pálffy, Balázs and Benedek, Csaba},
	booktitle = {2022 30th European Signal Processing Conference (EUSIPCO)},
	doi = {10.23919/EUSIPCO55093.2022.9909654},
	unique-id = {33240891},
	year = {2022},
	pages = {1786-1790},
	orcid-numbers = {Benedek, Csaba/0000-0003-3203-0741}
}

@article{MTMT:33229490,
	title = {Multi-sensorial Environment Perception in Urban Environment},
	url = {https://m2.mtmt.hu/api/publication/33229490},
	author = {Benedek, Csaba},
	doi = {10.1007/978-3-031-19650-8_1},
	journal-iso = {COMMUN COMPUT INFORM SCI},
	journal = {COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE},
	volume = {1667},
	unique-id = {33229490},
	issn = {1865-0929},
	year = {2022},
	eissn = {1865-0937},
	pages = {1-24},
	orcid-numbers = {Benedek, Csaba/0000-0003-3203-0741}
}