6 citations · 8 across the 11 of their papers we have counts for
12 papers
BRAVE-6D: Benchmark for Robotic Active Vision in 6DOF Pose Estimation
Philipp Ausserlechner, Bernhard Neuberger, Alessandro Scherl +3
Detecting and grasping small objects remains a significant challenge in robotics. Active vision, where the robot moves closer to the object, is an intuitive solution, yet comparing…
SCOPE: Semantic Conditioning for Sim2Real Category-Level Object Pose Estimation in Robotics
Peter Hönig, Stefan Thalhammer, Jean-Baptiste Weibel +2
Object manipulation requires accurate object pose estimation. In open environments, robots encounter unknown objects, which requires semantic understanding in order to generalize b…
OTAS: Open-vocabulary Token Alignment for Outdoor Segmentation
Simon Schwaiger, Stefan Thalhammer, Wilfried Wöber +1
Understanding open-world semantics is critical for robotic planning and control, particularly in unstructured outdoor environments. Existing vision-language mapping approaches typi…
ViT-VS: On the Applicability of Pretrained Vision Transformer Features for Generalizable Visual Servoing
Alessandro Scherl, Stefan Thalhammer, Bernhard Neuberger +2
Visual servoing enables robots to precisely position their end-effector relative to a target object. While classical methods rely on hand-crafted features and thus are universally…
Enhancing Transparent Object Pose Estimation: A Fusion of GDR-Net and Edge Detection
Tessa Pulli, Peter Hönig, Stefan Thalhammer +2
Object pose estimation of transparent objects remains a challenging task in the field of robot vision due to the immense influence of lighting, background, and reflections. However…
ReFlow6D: Refraction-Guided Transparent Object 6D Pose Estimation via Intermediate Representation Learning
Hrishikesh Gupta, Stefan Thalhammer, Jean-Baptiste Weibel +2
Transparent objects are ubiquitous in daily life, making their perception and robotics manipulation important. However, they present a major challenge due to their distinct refract…
Diffusion Features for Zero-Shot 6DoF Object Pose Estimation
Bernd Von Gimborn, Philipp Ausserlechner, Markus Vincze +1
Zero-shot object pose estimation enables the retrieval of object poses from images without necessitating object-specific training. In recent approaches this is facilitated by visio…
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…
UGV-CBRN: An Unmanned Ground Vehicle for Chemical, Biological, Radiological, and Nuclear Disaster Response
Simon Schwaiger, Lucas Muster, Georg Novotny +4
Robotic search and rescue (SAR) supports response teams by accelerating disaster assessment and by keeping operators away from hazardous environments. In the event of a chemical, b…
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…
Shape-biased Texture Agnostic Representations for Improved Textureless and Metallic Object Detection and 6D Pose Estimation
Peter Hönig, Stefan Thalhammer, Jean-Baptiste Weibel +2
Recent advances in machine learning have greatly benefited object detection and 6D pose estimation. However, textureless and metallic objects still pose a significant challenge due…
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…