{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/perception-for-autonomous-systems-paz","title":"Perception for Autonomous Systems (PAZ)","arxiv_id":"2010.14541","date":"2020-10-27","proceeding":null,"authors":["Octavio Arriaga","Matias Valdenegro-Toro","Mohandass Muthuraja","Sushma Devaramani","Frank Kirchner"],"abstract":"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.","url_abs":"https://arxiv.org/abs/2010.14541v1","url_pdf":"https://arxiv.org/pdf/2010.14541v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"perception-for-autonomous-systems-paz","repo_url":"https://github.com/oarriaga/paz","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"2d-object-detection","task_name":"2D Object Detection"},{"task_slug":"6d-pose-estimation-1","task_name":"6D Pose Estimation"},{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"emotion-classification","task_name":"Emotion Classification"},{"task_slug":"face-recognition","task_name":"Face Recognition"},{"task_slug":"instance-segmentation","task_name":"Instance Segmentation"},{"task_slug":"keypoint-estimation","task_name":"Keypoint Estimation"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}