2 citations · 3 across the 5 of their papers we have counts for
5 papers
From Words to Poses: Enhancing Novel Object Pose Estimation with Vision Language Models
Tessa Pulli, Stefan Thalhammer, Simon Schwaiger +1
Robots are increasingly envisioned to interact in real-world scenarios, where they must continuously adapt to new situations. To detect and grasp novel objects, zero-shot pose esti…
Improving 2D-3D Dense Correspondences with Diffusion Models for 6D Object Pose Estimation
Peter Hönig, Stefan Thalhammer, Markus Vincze
Estimating 2D-3D correspondences between RGB images and 3D space is a fundamental problem in 6D object pose estimation. Recent pose estimators use dense correspondence maps and Poi…
ZS6D: Zero-shot 6D Object Pose Estimation using Vision Transformers
Philipp Ausserlechner, David Haberger, Stefan Thalhammer +2
As robotic systems increasingly encounter complex and unconstrained real-world scenarios, there is a demand to recognize diverse objects. The state-of-the-art 6D object pose estima…
Self-supervised Vision Transformers for 3D Pose Estimation of Novel Objects
Stefan Thalhammer, Jean-Baptiste Weibel, Markus Vincze +1
Object pose estimation is important for object manipulation and scene understanding. In order to improve the general applicability of pose estimators, recent research focuses on pr…
COPE: End-to-end trainable Constant Runtime Object Pose Estimation
Stefan Thalhammer, Timothy Patten, Markus Vincze
State-of-the-art object pose estimation handles multiple instances in a test image by using multi-model formulations: detection as a first stage and then separately trained network…