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Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

Sundermeyer, Martin and Marton, Zoltan-Csaba and Durner, Maximilian and Brucker, Manuel and Triebel, Rudolph (2018) Implicit 3D Orientation Learning for 6D Object Detection from RGB Images. In: Proceedings of the European Conference on Computer Vision (ECCV) 2018, pp. 699-715. Springer. European Conference on Computer Vision, 10-13 Sep 2018, Munich, Germany.

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Official URL: https://eccv2018.org/

Abstract

We propose a real-time RGB-based pipeline for object detection and 6D pose estimation. Our novel 3D orientation estimation is based on a variant of the Denoising Autoencoder that is trained on simulated views of a 3D model using Domain Randomization. This so-called Augmented Autoencoder has several advantages over existing methods: It does not require real, pose-annotated training data, generalizes to various test sensors and inherently handles object and view symmetries. Instead of learning an explicit mapping from input images to object poses, it provides an implicit representation of object orientations defined by samples in a latent space. Experiments on the T-LESS and LineMOD datasets show that our method outperforms similar model-based approaches and competes with state-of-the art approaches that require real pose-annotated images.

Item URL in elib:https://elib.dlr.de/122011/
Document Type:Conference or Workshop Item (Poster, Keynote)
Title:Implicit 3D Orientation Learning for 6D Object Detection from RGB Images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Sundermeyer, Martinmartin.sundermeyer (at) dlr.dehttps://orcid.org/0000-0003-0587-9643
Marton, Zoltan-CsabaZoltan.Marton (at) dlr.dehttps://orcid.org/0000-0002-3035-493X
Durner, MaximilianMaximilian.Durner (at) dlr.dehttps://orcid.org/0000-0001-8885-5334
Brucker, Manuelmanuel.brucker (at) dlr.dehttps://orcid.org/0000-0001-6370-2753
Triebel, Rudolphrudolph.triebel (at) dlr.dehttps://orcid.org/0000-0002-7975-036X
Date:10 September 2018
Journal or Publication Title:Proceedings of the European Conference on Computer Vision (ECCV) 2018
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 699-715
Publisher:Springer
Status:Published
Keywords:6D Object Detection, Pose Estimation, Domain Randomization, Autoencoder, Synthetic Data, Pose Ambiguity, Symmetries
Event Title:European Conference on Computer Vision
Event Location:Munich, Germany
Event Type:international Conference
Event Dates:10-13 Sep 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Multisensorielle Weltmodellierung
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition
Deposited By: Sundermeyer, Martin
Deposited On:30 Nov 2018 00:39
Last Modified:31 Jul 2019 20:19

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