5 papers
LiftNav: Path Planning via Semantic Lifting in TSDF-Guided Gaussian Splatting
Hannah Schieber, Dominik Frischmann, Victor Schaack +2
Autonomous robots in unknown indoor environments require both reliable collision avoidance and object-level understanding. Classical representations such as TSDF support safe plann…
Supercharging Thermal Gaussian Splatting with Depth Estimation
Manoj Biswanath, Chenxin Cai, Hannah Schieber +2
Efficient and robust 3D scene representation is crucial in autonomous driving, robotics, and related fields. While RGB images provide valuable content for 3D reconstruction, other…
CoRe-GS: Coarse-to-Refined Gaussian Splatting with Semantic Object Focus
Hannah Schieber, Dominik Frischmann, Victor Schaack +4
Fast and efficient 3D reconstruction is essential for time-critical robotic applications such as tele-guidance and disaster response, where operators must rapidly analyze specific…
Locality-Sensitive Hashing for Efficient Hard Negative Sampling in Contrastive Learning
Fabian Deuser, Philipp Hausenblas, Hannah Schieber +3
Contrastive learning is a representational learning paradigm in which a neural network maps data elements to feature vectors. It improves the feature space by forming lots with an…
DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields
Nicolas Schischka, Hannah Schieber, Mert Asim Karaoglu +6
The accurate reconstruction of dynamic scenes with neural radiance fields is significantly dependent on the estimation of camera poses. Widely used structure-from-motion pipelines…