6 citations · 11 across the 15 of their papers we have counts for
16 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…
Per-Group Error, Not Total MSE: Fine-Tuning Vision-Language-Action Models for 11-DoF Mobile Manipulation
Pau Montagut Bofi, Mario García Blasco, Tessa Pulli +1
Fine-tuning Vision-Language-Action (VLA) models for mobile manipulators with heterogeneous joint spaces can produce a counterintuitive result: the checkpoint with the lowest aggreg…
OSCAR: Open-Set CAD Retrieval from a Language Prompt and a Single Image
Tessa Pulli, Jean-Baptiste Weibel, Peter Hönig +3
6D object pose estimation plays a crucial role in scene understanding for applications such as robotics and augmented reality. To support the needs of ever-changing object sets in…
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…
Sim2Real Transfer for Vision-Based Grasp Verification
Pau Amargant, Peter Hönig, Markus Vincze
The verification of successful grasps is a crucial aspect of robot manipulation, particularly when handling deformable objects. Traditional methods relying on force and tactile sen…
LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household Robotics
Marc Glocker, Peter Hönig, Matthias Hirschmanner +1
We present an embodied robotic system with an LLM-driven agent-orchestration architecture for autonomous household object management. The system integrates memory-augmented task pl…
Category-Level and Open-Set Object Pose Estimation for Robotics
Peter Hönig, Matthias Hirschmanner, Markus Vincze
Object pose estimation enables a variety of tasks in computer vision and robotics, including scene understanding and robotic grasping. The complexity of a pose estimation task depe…
Multi-Modal 3D Mesh Reconstruction from Images and Text
Melvin Reka, Tessa Pulli, Markus Vincze
6D object pose estimation for unseen objects is essential in robotics but traditionally relies on trained models that require large datasets, high computational costs, and struggle…
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…
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…
Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers
Gerald Ebmer, Adam Loch, Minh Nhat Vu +5
Real-time applications for autonomous operations depend largely on fast and robust vision-based localization systems. Since image processing tasks require processing large amounts…
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…