| A self-assessment stereo capture model applicable to the internet of things Y Lin, J Yang, Z Lv, W Wei, H Song Sensors 15 (8), 20925-20944, 2015 | 208 | 2015 |
| Deep Hough-Transform line priors Y Lin, SL Pintea, JC Van Gemert Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 94 | 2020 |
| Quality index for stereoscopic images by jointly evaluating cyclopean amplitude and cyclopean phase Y Lin, J Yang, W Lu, Q Meng, Z Lv, H Song IEEE Journal of Selected Topics in Signal Processing 11 (1), 89-101, 2016 | 42 | 2016 |
| Deep vanishing point detection: Geometric priors make dataset variations vanish Y Lin, R Wiersma, SL Pintea, K Hildebrandt, E Eisemann, JC van Gemert Conference on Computer Vision and Pattern Recognition, 2022 | 28 | 2022 |
| A step towards understanding why classification helps regression SL Pintea, Y Lin, J Dijkstra, JC van Gemert Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 14 | 2023 |
| Semi-Supervised Lane Detection With Deep Hough Transform Y Lin, SL Pintea, J van Gemert IEEE International Conference on Image Processing (ICIP), 2021 | 13 | 2021 |
| ICP-Flow: Lidar scene flow estimation with icp Y Lin, H Caesar Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 12 | 2024 |
| BaSAL: Size-Balanced Warm Start Active Learning for LiDAR Semantic Segmentation J Wei, Y Lin, H Caesar 2024 IEEE International Conference on Robotics and Automation (ICRA), 18258 …, 2024 | 4 | 2024 |
| Bosch street dataset: A multi-modal dataset with imaging radar for automated driving K Armanious, M Quach, M Ulrich, T Winterling, J Friesen, S Braun, ... arXiv preprint arXiv:2407.12803, 2024 | 2 | 2024 |
| Investigating transformers in the decomposition of polygonal shapes as point collections A Alfieri, Y Lin, JC van Gemert Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 2 | 2021 |
| NeRD++: Improved 3D-mirror symmetry learning from a single image Y Lin, SL Pintea, J van Gemert BMVC 2022, 0 | 1* | |
| Improving the Performance of Object Counting Using Training Images in the Frequency Domain D Rogmans, Y Lin, S Pintea | | |
| Can object-specific frequency information from labeled data improve a CNN’s robustness to adversarial attacks? N Mertzanis, N Tömen, Y Lin, A Lengyel | | |
| Injecting prior frequency information in DETR for wheat head detection A Prundeanu, Y Lin, A Lengyel, S Pintea | | |
Silvia-Laura PinteaComputer vision researcherZweryfikowany adres z lumc.nl