6 papers
CylinderDepth: Cylindrical Spatial Attention for Multi-View Consistent Self-Supervised Surround Depth Estimation
Samer Abualhanud, Christian Grannemann, Max Mehltretter
Self-supervised surround-view depth estimation enables dense, low-cost 3D perception with a 360° field of view from multiple minimally overlapping images. Yet, most existing metho…
Semantic Segmentation of Textured Non-manifold 3D Meshes using Transformers
Mohammadreza Heidarianbaei, Max Mehltretter, Franz Rottensteiner
Textured 3D meshes jointly represent geometry, topology, and appearance, yet their irregular structure poses significant challenges for deep-learning-based semantic segmentation. W…
Open-Vocabulary Semantic Segmentation in Remote Sensing via Hierarchical Attention Masking and Model Composition
Mohammadreza Heidarianbaei, Mareike Dorozynski, Hubert Kanyamahanga +2
In this paper, we propose ReSeg-CLIP, a new training-free Open-Vocabulary Semantic Segmentation method for remote sensing data. To compensate for the problems of vision language mo…
Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene Semantic Segmentation
Hanieh Shojaei, Qianqian Zou, Max Mehltretter
Safe navigation in new environments requires autonomous vehicles and robots to accurately interpret their surroundings, relying on LiDAR scene segmentation, out-of-distribution (OO…
Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications
Markus Hillemann, Robert Langendörfer, Max Heiken +6
Neural Radiance Fields (NeRFs) have become a rapidly growing research field with the potential to revolutionize typical photogrammetric workflows, such as those used for 3D scene r…
Image-based Deep Learning for the time-dependent prediction of fresh concrete properties
Max Meyer, Amadeus Langer, Max Mehltretter +5
Increasing the degree of digitisation and automation in the concrete production process can play a crucial role in reducing the CO emissions that are associated with the produc…