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Perception for Autonomous Systems (PAZ)

  • In this paper we introduce the Perception for Autonomous Systems (PAZ) software library. PAZ is a hierarchical perception library that allow users to manipulate multiple levels of abstraction in accordance to their requirements or skill level. More specifically, PAZ is divided into three hierarchical levels which we refer to as pipelines, processors, and backends. These abstractions allows users to compose functions in a hierarchical modular scheme that can be applied for preprocessing, data-augmentation, prediction and postprocessing of inputs and outputs of machine learning (ML) models. PAZ uses these abstractions to build reusable training and prediction pipelines for multiple robot perception tasks such as: 2D keypoint estimation, 2D object detection, 3D keypoint discovery, 6D pose estimation, emotion classification, face recognition, instance segmentation, and attention mechanisms.

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Metadaten
Document Type:Preprint
Language:English
Author:Octavio Arriaga, Matias Valdenegro-Toro, Mohandass Muthuraja, Sushma Devaramani, Frank Kirchner
Number of pages:7
DOI:https://doi.org/10.48550/arXiv.2010.14541
ArXiv Id:http://arxiv.org/abs/2010.14541
Publisher:arXiv
Date of first publication:2020/10/27
Funding:This work was supported throughtwo grants of the German Federal Ministry of Economics and Energy during the ProjectsTransFIT and KiMMI-SF [BMWi, FKZ 50 RA 1703, and FKZ 50 RA 2022].
Keyword:Deep Learning; Robot Perception; computer vision
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2020/11/04