Publications

Mehltretter, M. (2021): Uncertainty Estimation for Dense Stereo Matching using Bayesian Deep Learning. In: Deutsche Geodätische Kommission Reihe C, Nr. 878, ISSN 0065-5325 (ebenfalls in: Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz Universität Hannover, Nr. 378, ISSN 0174-1454) | File |

El Amrani Abouelassad, S., Mehltretter, M. & Rottensteiner, F. (2024): Monocular Pose and Shape Reconstruction of Vehicles in UAV Imagery using a multi-task CNN. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, Vol. 92, 499-516.
DOI: 10.1007/s41064-024-00311-0

Trusheim, P., Mehltretter, M., Rottensteiner, F., & Heipke, C. (2024): Cooperative Image Orientation with Dynamic Objects. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, Vol. 92, 461–481.
DOI: 10.1007/s41064-024-00296-w

Iqbal, W., Paffenholz, J.-A., Mehltretter, M. (2023): Guiding Deep Learning with Expert Knowledge for Dense Stereo Matching. In: PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science.
DOI: 10.1007/s41064-023-00252-0

Mehltretter M., Heipke C. (2021): Aleatoric uncertainty estimation for dense stereo matching via CNN-based cost volume analysis. . ISPRS Journal of Photogrammetry and Remote Sensing (171), 63-75.
DOI: 10.1016/j.isprsjprs.2020.11.003

Schrapel M., Rohs M., Mehltretter M., Heipke C. (2022): MOBILISE: Mobilität zwischen Mensch und Technik. VDI/VDE Hannover Technik und Leben, 1/22, p. 7 More info

Meyer, M., Langer, A., Mehltretter, M., Beyer, D., Coenen, M., Schack, T., Haist, M., Heipke, C. (2024): Image-based deep learning for the time-dependent prediction of fresh concrete properties. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-2-2024, pp. 145–152.
DOI: 10.5194/isprs-annals-X-2-2024-145-2024

Nguyen, T., Mehltretter, M., Rottensteiner, F. (2024): Depth-aware panoptic segmentation. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-2-2024, pp. 153–161.
DOI: 10.5194/isprs-annals-X-2-2024-153-2024

El Amrani Abouelassad, S., Mehltretter, M., Rottensteiner, F. (2023): Vehicle pose and shape estimation in UAV imagery using a CNN. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1/W1-2023, pp. 935–944.
DOI: 10.5194/isprs-annals-X-1-W1-2023-935-2023

Mehltretter, M. (2022): Joint Estimation of Depth and its Uncertainty from Stereo Images using Bayesian Deep Learning. In: ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences , V-2-2022, pp. 69-78.
DOI: 10.5194/isprs-annals-V-2-2022-69-2022

Trusheim, P., Mehltretter M., Rottensteiner F., Heipke C. (2022): Cooperative image orientation considering dynamic objects. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2022, pp. 169–177.
DOI: 10.5194/isprs-annals-V-1-2022-169-2022

Zhong, Z., Mehltretter, M (2021): Mixed Probability Models for Aleatoric Uncertainty Estimation in the Context of Dense Stereo Matching, ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2021, 17-26
DOI: 10.5194/isprs-annals-V-2-2021-17-2021

Höllmann M., Mehltretter M., Heipke C. (2020): Geometry-based regularisation for dense image matching via uncertainty-driven depth propagation. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020, 151–159.
DOI: 10.5194/isprs-annals-V-2-2020-151-2020

Mehltretter, M. (2020): Uncertainty Estimation for End-To-End Learned Dense Stereo Matching via Probabilistic Deep Learning, ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2020, 161-169
DOI: 10.5194/isprs-annals-V-2-2020-161-2020

Mehltretter, M.; Heipke C. (2019): CNN-based Cost Volume Analysis as Confidence Measure for Dense Matching, ICCV, 2nd Workshop on 3D Reconstruction in the Wild (3DRW2019), Proceedings. | File |

Behmann, N.; Mehltretter, M.; Kleinschmidt, S. P.; Wagner, B.; Heipke, C.; Blume, H. (2018): GPU-enhanced Multimodal Dense Matching. 2018 IEEE Nordic Circuits and Systems Conference (NORCAS): NORCHIP and International Symposium of System-on-Chip (SoC). | File | More info
DOI: 10.1109/NORCHIP.2018.8573526

Mehltretter, M.; Kleinschmidt, S.P.; Wagner, B.; Heipke, C. (2018): Multimodal dense stereo matching. In: Bronx T., Bruhn A. (Eds.): Pattern recognition – 40th German Conference GCPR Stuttgart, LNCS 11269, Springer, 407-421. | File |
DOI: doi.org/10.1007/978-3-030-12939-2_28

Hillemann, M., Langendörfer, R., Heiken, M., Mehltretter, M., Schenk, A., Weinmann, M., Hinz, S., Heipke, C., Ulrich, M. (2024): Novel view synthesis with neural radiance fields for industrial robot applications. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2-2024, pp. 137–144.
DOI: 10.5194/isprs-archives-XLVIII-2-2024-137-2024

Ali, R., Mehltretter, M., Heipke, C. (2023): Integrating motion priors for end-to-end attention-based multi-object tracking. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1/W2-2023, 1619–1626.
DOI: 10.5194/isprs-archives-XLVIII-1-W2-2023-1619-2023

Ali, R., Dorozynski, M., Stracke, J., and Mehltretter, M. (2022): DEEP LEARNING-BASED TRACKING OF MULTIPLE OBJECTS IN THE CONTEXT OF FARM ANIMAL ETHOLOGY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 509–516
DOI: 10.5194/isprs-archives-XLIII-B2-2022-509-2022

Heinrich, K., Mehltretter, M. (2021): Learning Multi-Modal Features for Dense Matching-Based Confidence Estimation, ISPRS Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2021, 91-99
DOI: 10.5194/isprs-archives-XLIII-B2-2021-91-2021

Mehltretter, M., Heipke, C. (2018): Illumination Invariant Dense Image Matching based on Sparse Features. 38. Wissenschaftlich-Technische Jahrestagung der DGPF und PFGK18 Tagung in München, Band 27, 584-596. More info