Short Biography

I studied computer science at the Technical University of Darmstadt and successfully graduated with a Master of Science in 2017. Since 2017, I am working as a research scientist at the Institute of Photogrammetry und GeoInformation (IPI) at Leibniz University Hannover. I received a doctoral degree there with distinction in 2021 on the topic of Uncertainty Estimation for Dense Stereo Matching using Bayesian Deep Learning. From 2021 to 2023, I was a postdoc in the DFG funded Research Training Group i.c.sens. Since 2022, I am the Leader of the Photogrammetric Computer Vision Group at IPI.

I am actively involved in scientific panels: On the one hand, I am the secretary of the working group II/3 "3D scene reconstruction for modeling & mapping" of the International Society for Photogrammetry and Remote Sensing (ISPRS). On the other hand, I am the leader of the working group "Image Analysis and Computer Vision" of the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF).

Besides my research, I am particularly interested in politics. I have been a member of a democratic party for many years and I am actively involved at municipal level. I am also an enthusiastic sports shooter and a licensed trainer.

Research

Research Focus

  • 3D Reconstruction
  • Machine Learning / Deep Learning
  • Semantic Scene Understanding
  • Uncertainty Estimation
  • Tracking of Dynamic Objects

Projects

Integrity and Collaboration in Dynamic Sensor Networks (i.c.sens)
The Research Training Group 2159 "Integrity and Collaboration in Dynamic Sensor Networks" (i.c.sens) is a joint research and doctoral program at Leibniz University Hannover funded by the German Research Foundation (DFG). In the context of this research training group, nine PhD students and one PostDoc investigate the aspects of trustworthiness of automated and autonomous systems (integrity) and collaboration betwenn multiple such systems as well as their individual sensors. [Website]

MOBILISE – Mobility in Engineering and Science: Mobile Human
Within the framework of the joint master plan "MOBILISE - Mobility in Engineering and Science", two universities of Lower Saxony, Leibniz University Hannover and TU Braunschweig, cooperate in the field of "Digitization". The field "Mobile Human: Intelligent Mobility in the Balance of Autonomy, Linkage and Security" under the direction of Prof. Kurt Schneider brings together a group of junior researchers investigating seminal, previously unestablished topics of social relevance. A total of 13 professorships from five LUH faculties with their specific, complementary areas of focus are involved in the project. [Website]

Publications

2025:
Heidarianbaei, M., Mehltretter, M., Rottensteiner, F. (2025): NoMeFormer: Non-Manifold Mesh Transformer. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences.
Ali, R., Heipke, C., Mehltretter, M. (2025): Integrating Intrinsic and Extrinsic Camera Parameters and Image Features for Robust Multi-View Multi-Object 3D Pedestrian Tracking. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences.
2024:
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. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, X-2-2024, pp. 145-152. [More]
Nguyen, T., Mehltretter, M., Rottensteiner, F. (2024): Depth-aware Panoptic Segmentation. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, X-2-2024, pp. 153-161. [More]
Hillemann, M., Heiken, M., Mehltretter, M., Langendörfer, R., Schenk, A., Weinmann, M., Hinz, S., Heipke, C., Ulrich, M. (2024): Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications. ISPRS Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-2-2024, pp. 137-144. [More]
Meyer, M., Langer, A., Mehltretter, M., Beyer, D., Coenen, M., Schack, T., Haist, M., Heipke, C. (2024): Fresh Concrete Properties from Stereoscopic Image Sequences. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 92, pp. 517-529. [More]
Trusheim, P., Mehltretter, M., Rottensteiner, F., Heipke, C. (2024): Cooperative Image Orientation with Dynamic Objects. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 92, pp. 461-481. [More]
Abualhanud, S., Erahan, E., Mehltretter, M. (2024): Self-Supervised 3D Semantic Occupancy Prediction from Multi-View 2D Surround Images. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 92, pp. 483-498. [More]
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, 92, pp. 499-516. [More]
Shojaei Miandashti, H., Zou, Q., Mehltretter, M. (2024): Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene Semantic Segmentation. Proceedings of the European Conference on Computer Vision Workshops. [More]
2023:
Ali, R., Mehltretter, M., Heipke, C. (2023): Integrating Motion Priors for End-To-End Attention-based Multi-Object Tracking. ISPRS Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-1/W2-2023, pp. 1619-1626. [More]
El Amrani Abouelassad, S., Mehltretter, M., Rottensteiner, F. (2023): Vehicle Pose and Shape Estimation in UAV Imagery Using a CNN. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, X-1/W1-2023, pp. 935-944. [More]
Iqbal, W., Paffenholz, J., Mehltretter, M. (2023): Guiding Deep Learning with Expert Knowledge for Dense Stereo Matching. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 91, pp. 365-380. [More]
2022:
Mehltretter, M. (2022): Joint Estimation of Depth and its Uncertainty from Stereo Images Using Bayesian Deep Learning. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2022, pp. 69-78. [More]
Trusheim, P., Mehltretter, M., Rottensteiner, F., Heipke, C. (2022): Cooperative Visual Localisation Considering Dynamic Objects. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, V-1-2022, pp. 169-177. [More]
Ali, R., Dorozynski, M., Stracke, J., Mehltretter, M. (2022): Deep Learning-based Tracking of Multiple Objects in the Context of Farm Animal Ethology. ISPRS Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022, pp. 509-516. [More]
2021:
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, pp. 63-75. [More]
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, pp. 17-26. [More]
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, pp. 91-99. [More]
Mehltretter, M. (2021): Uncertainty Estimation for Dense Stereo Matching Using Bayesian Deep Learning. PhD thesis. [More]
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, pp. 161-169. [More]
Höllmann, M., Mehltretter, M., Heipke, C. (2020): Geometry-Based Regularisation for Dense Image Matching via Uncertainty-Driven Depth Propagation. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2020, pp. 151-159. [More]
2019:
Mehltretter, M., Heipke, C. (2019): CNN-based Cost Volume Analysis as Confidence Measure for Dense Matching. Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 2070-2079. [More]
2018:
Mehltretter, M., Heipke, C. (2018): Illumination Invariant Dense Image Matching based on Sparse Features. 38. Wissenschaftlich-Technische Jahrestagung der DGPF und PFGK18 Tagung, pp. 584-596. [More]
Behmann, N., Mehltretter, M., Kleinschmidt, S., Wagner, B., Heipke, C., Blume, H. (2018): GPU-enhanced Multimodal Dense Matching. IEEE Nordic Circuits and Systems Conference: NORCHIP and International Symposium of System-on-Chip. [More]
Mehltretter, M., Kleinschmidt, S., Wagner, B., Heipke, C. (2018): Multimodal Dense Stereo Matching. Proceedings of the German Conference on Pattern Recognition, pp. 407-421. [More]

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