Search Results for author: Markus Vincze

Found 30 papers, 13 papers with code

Improving 2D-3D Dense Correspondences with Diffusion Models for 6D Object Pose Estimation

no code implementations9 Feb 2024 Peter Hönig, Stefan Thalhammer, Markus Vincze

In this study, we compare image-to-image translation networks based on GANs and diffusion models for the downstream task of 6D object pose estimation.

6D Pose Estimation using RGB Benchmarking +3

Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers

no code implementations25 Oct 2023 Gerald Ebmer, Adam Loch, Minh Nhat Vu, Germain Haessig, Roberto Mecca, Markus Vincze, Christian Hartl-Nesic, Andreas Kugi

Experimental results in static and dynamic scenarios are presented to demonstrate the performance of the proposed approach in terms of computational speed and absolute accuracy, using the OptiTrack system as the basis for measurement.

Pose Estimation

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

no code implementations21 Sep 2023 Philipp Ausserlechner, David Haberger, Stefan Thalhammer, Jean-Baptiste Weibel, Markus Vincze

The state-of-the-art 6D object pose estimation methods rely on object-specific training and therefore do not generalize to unseen objects.

6D Pose Estimation 6D Pose Estimation using RGB +2

TrackAgent: 6D Object Tracking via Reinforcement Learning

no code implementations28 Jul 2023 Konstantin Röhrl, Dominik Bauer, Timothy Patten, Markus Vincze

Tracking an object's 6D pose, while either the object itself or the observing camera is moving, is important for many robotics and augmented reality applications.

Object Object Tracking +2

Self-supervised Vision Transformers for 3D Pose Estimation of Novel Objects

1 code implementation31 May 2023 Stefan Thalhammer, Jean-Baptiste Weibel, Markus Vincze, Jose Garcia-Rodriguez

This work evaluates and demonstrates the differences between self-supervised CNNs and Vision Transformers for deep template matching.

3D Pose Estimation Contrastive Learning +4

Open Challenges for Monocular Single-shot 6D Object Pose Estimation

no code implementations23 Feb 2023 Stefan Thalhammer, Peter Hönig, Jean-Baptiste Weibel, Markus Vincze

Object pose estimation is a non-trivial task that enables robotic manipulation, bin picking, augmented reality, and scene understanding, to name a few use cases.

6D Pose Estimation using RGB Object +2

Grasping the Inconspicuous

no code implementations15 Nov 2022 Hrishikesh Gupta, Stefan Thalhammer, Markus Leitner, Markus Vincze

Towards this, we study deep learning 6D pose estimation from RGB images only for transparent object grasping.

6D Pose Estimation Object +1

COPE: End-to-end trainable Constant Runtime Object Pose Estimation

no code implementations18 Aug 2022 Stefan Thalhammer, Timothy Patten, Markus Vincze

We present an approach that learns an intermediate geometric representation of multiple objects to directly regress 6D poses of all instances in a test image.

6D Pose Estimation using RGB Object

SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement

1 code implementation1 Jan 2022 Dominik Bauer, Timothy Patten, Markus Vincze

Observational noise, inaccurate segmentation and ambiguity due to symmetry and occlusion lead to inaccurate object pose estimates.


Event-Based high-speed low-latency fiducial marker tracking

no code implementations12 Oct 2021 Adam Loch, Germain Haessig, Markus Vincze

Motion and dynamic environments, especially under challenging lighting conditions, are still an open issue for robust robotic applications.

Pose Estimation Vocal Bursts Intensity Prediction

UnrealROX+: An Improved Tool for Acquiring Synthetic Data from Virtual 3D Environments

1 code implementation23 Apr 2021 Pablo Martinez-Gonzalez, Sergiu Oprea, John Alejandro Castro-Vargas, Alberto Garcia-Garcia, Sergio Orts-Escolano, Jose Garcia-Rodriguez, Markus Vincze

Synthetic data generation has become essential in last years for feeding data-driven algorithms, which surpassed traditional techniques performance in almost every computer vision problem.

Depth Estimation object-detection +3

ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning

2 code implementations CVPR 2021 Dominik Bauer, Timothy Patten, Markus Vincze

Point cloud registration is a common step in many 3D computer vision tasks such as object pose estimation, where a 3D model is aligned to an observation.

Imitation Learning Point Cloud Registration +3

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

1 code implementation30 Oct 2020 Stefan Thalhammer, Markus Leitner, Timothy Patten, Markus Vincze

We also perform grasping experiments in the real world to demonstrate the advantage of using synthetic data to generalize to novel environments.

Decoder Pose Estimation

Neural Object Learning for 6D Pose Estimation Using a Few Cluttered Images

1 code implementation ECCV 2020 Kiru Park, Timothy Patten, Markus Vincze

Recent methods for 6D pose estimation of objects assume either textured 3D models or real images that cover the entire range of target poses.

6D Pose Estimation

Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition

3 code implementations21 Apr 2020 Mohammad Reza Loghmani, Luca Robbiano, Mirco Planamente, Kiru Park, Barbara Caputo, Markus Vincze

Unsupervised Domain Adaptation (DA) exploits the supervision of a label-rich source dataset to make predictions on an unlabeled target dataset by aligning the two data distributions.

Object Categorization Object Recognition +1

Robot Perception of Static and Dynamic Objects with an Autonomous Floor Scrubber

1 code implementation24 Feb 2020 Zhi Yan, Simon Schreiberhuber, Georg Halmetschlager, Tom Duckett, Markus Vincze, Nicola Bellotto

The proposed system is based on multiple sensors including 3D and 2D lidar, two RGB-D cameras and a stereo camera.


DGCM-Net: Dense Geometrical Correspondence Matching Network for Incremental Experience-based Robotic Grasping

no code implementations15 Jan 2020 Timothy Patten, Kiru Park, Markus Vincze

This article presents a method for grasping novel objects by learning from experience.


Addressing the Sim2Real Gap in Robotic 3D Object Classification

no code implementations28 Oct 2019 Jean-Baptiste Weibel, Timothy Patten, Markus Vincze

In this work, we examine this gap in a robotic context by specifically addressing the problem of classification when transferring from artificial CAD models to real reconstructed objects.

3D Object Classification Classification +3

VeREFINE: Integrating Object Pose Verification with Physics-guided Iterative Refinement

1 code implementation12 Sep 2019 Dominik Bauer, Timothy Patten, Markus Vincze

The generality of the approach is shown by using three state-of-the-art pose estimators and three baseline refiners.

Object Pose Estimation

EasyLabel: A Semi-Automatic Pixel-wise Object Annotation Tool for Creating Robotic RGB-D Datasets

no code implementations5 Feb 2019 Markus Suchi, Timothy Patten, David Fischinger, Markus Vincze

This paper presents the EasyLabel tool for easily acquiring high quality ground truth annotation of objects at the pixel-level in densely cluttered scenes.

Object Semantic Segmentation

Recurrent Convolutional Fusion for RGB-D Object Recognition

1 code implementation5 Jun 2018 Mohammad Reza Loghmani, Mirco Planamente, Barbara Caputo, Markus Vincze

Providing machines with the ability to recognize objects like humans has always been one of the primary goals of machine vision.

Object Object Categorization +1

High Dynamic Range SLAM with Map-Aware Exposure Time Control

1 code implementation20 Apr 2018 Sergey V. Alexandrov, Johann Prankl, Michael Zillich, Markus Vincze

The research in dense online 3D mapping is mostly focused on the geometrical accuracy and spatial extent of the reconstructions.

Vocal Bursts Intensity Prediction

Recognizing Objects In-the-wild: Where Do We Stand?

no code implementations18 Sep 2017 Mohammad Reza Loghmani, Barbara Caputo, Markus Vincze

The ability to recognize objects is an essential skill for a robotic system acting in human-populated environments.

Object Object Recognition

Using Dimension Reduction to Improve the Classification of High-dimensional Data

no code implementations26 May 2015 Andreas Grünauer, Markus Vincze

In this work we show that the classification performance of high-dimensional structural MRI data with only a small set of training examples is improved by the usage of dimension reduction methods.

Dimensionality Reduction feature selection +2

Object Modelling with a Handheld RGB-D Camera

no code implementations21 May 2015 Aitor Aldoma, Johann Prankl, Alexander Svejda, Markus Vincze

This work presents a flexible system to reconstruct 3D models of objects captured with an RGB-D sensor.

Human-Object Interaction Detection Object +1

Find my mug: Efficient object search with a mobile robot using semantic segmentation

no code implementations23 Apr 2014 Daniel Wolf, Markus Bajones, Johann Prankl, Markus Vincze

In this paper, we propose an efficient semantic segmentation framework for indoor scenes, tailored to the application on a mobile robot.

Segmentation Semantic Segmentation

Cannot find the paper you are looking for? You can Submit a new open access paper.