Stefan Thalhammer

InstantPose: Zero-Shot Instance-Level 6D Pose Estimation from a Single View

Object pose estimation using visual data is crucial for robotic interaction with the environment. Many existing instance-level methods are restricted by their requirements for 3D CAD models or multiple object views, which limits their flexibility and generalizability. Overcoming this limitation is c…

OTAS: Open-Vocabulary Token Alignment for Outdoor Segmentation

InstantPose: Zero-Shot Instance-Level 6D Pose Estimation From a Single View

Object pose estimation using visual data is crucial for robotic interaction with the environment. Many existing instance-level methods are restricted by their requirements for 3D CAD models or multiple object views, which limits their flexibility and generalizability. Overcoming this limitation is c

ViT-VS: On the Applicability of Pretrained Vision Transformer Features for Generalizable Visual Servoing

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 applicable without task-specific training, they often struggle with occlusions and environmental variations, whereas lea

EdgeSoil 2.0 – Soil Analyzer Using Convolutional Neural Network and Camera Imaging for Agricultural Robotics

Soil is the most important building element of agriculture and its analysis is crucial for healthy plants and a high crop yield. But apart from its importance, soil analysis is a tedious and time-consuming task. This paper presents EdgeSoil 2.0, a non-invasive, accurate, and real-time robotic system…

ReFlow6D: Refraction-Guided Transparent Object 6D Pose Estimation via Intermediate Representation Learning

Transparent objects are ubiquitous in daily life, making their perception and robotics manipulation important. However, they present a major challenge due to their distinct refractive and reflective properties when it comes to accurately estimating the 6D pose. To solve this, we present <italic xmln

ZS6D: Zero-shot 6D Object Pose Estimation using Vision Transformers

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 estimation methods rely on object-specific training and therefore do not generalize to unseen objects. Recent novel object pos…

PyraPose: Feature Pyramids for Fast and Accurate Object Pose Estimation under Domain Shift

Object pose estimation enables robots to understand and interact with their environments. Training with synthetic data is necessary in order to adapt to novel situations. Unfortunately, pose estimation under domain shift, i.e., training on synthetic data and testing in the real world, is challenging…