| COVID detection and severity prediction with 3D-ConvNeXt and custom pretrainings D Kienzle, J Lorenz, R Schön, K Ludwig, R Lienhart European Conference on Computer Vision, 500-516, 2022 | 8 | 2022 |
| Detecting arbitrary keypoints on limbs and skis with sparse partly correct segmentation masks K Ludwig, D Kienzle, J Lorenz, R Lienhart Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 7 | 2023 |
| Recognition of freely selected keypoints on human limbs K Ludwig, D Kienzle, R Lienhart Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 4 | 2022 |
| Haystack: A panoptic scene graph dataset to evaluate rare predicate classes J Lorenz, F Barthel, D Kienzle, R Lienhart Proceedings of the IEEE/CVF International Conference on Computer Vision, 62-70, 2023 | 2 | 2023 |
| The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data LH Boulogne, J Lorenz, D Kienzle, R Schön, K Ludwig, R Lienhart, ... Medical Image Analysis 97, 103230, 2024 | 1 | 2024 |
| Custom pretrainings and adapted 3d-convnext architecture for covid detection and severity prediction D Kienzle, J Lorenz, R Schön, K Ludwig, R Lienhart CoRR, 2022 | 1 | 2022 |
| WSESeg: Introducing a Dataset for the Segmentation of Winter Sports Equipment with a Baseline for Interactive Segmentation R Schön, D Kienzle, R Lienhart arXiv preprint arXiv:2407.09288, 2024 | | 2024 |
| A Fair Ranking and New Model for Panoptic Scene Graph Generation J Lorenz, A Pest, D Kienzle, K Ludwig, R Lienhart arXiv preprint arXiv:2407.09216, 2024 | | 2024 |
| Segformer++: Efficient Token-Merging Strategies for High-Resolution Semantic Segmentation D Kienzle, M Kantonis, R Schön, R Lienhart arXiv preprint arXiv:2405.14467, 2024 | | 2024 |
| Towards learning monocular 3D object localization from 2D labels using the physical laws of motion D Kienzle, K Ludwig, J Lorenz, R Lienhart 2024 International Conference on 3D Vision (3DV), 1564-1573, 2024 | | 2024 |
Rainer LienhartProfessor of Computer Science, University of Augsburg在 informatik.uni-augsburg.de 的电子邮件经过验证
