{"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/real-time-object-pose-estimation-with-pose","title":"Real-Time Object Pose Estimation with Pose Interpreter Networks","arxiv_id":"1808.01099","date":"2018-08-03","proceeding":null,"authors":["Jimmy Wu","Bolei Zhou","Rebecca Russell","Vincent Kee","Syler Wagner","Mitchell Hebert","Antonio Torralba","David M. S. Johnson"],"abstract":"In this work, we introduce pose interpreter networks for 6-DoF object pose\nestimation. In contrast to other CNN-based approaches to pose estimation that\nrequire expensively annotated object pose data, our pose interpreter network is\ntrained entirely on synthetic pose data. We use object masks as an intermediate\nrepresentation to bridge real and synthetic. We show that when combined with a\nsegmentation model trained on RGB images, our synthetically trained pose\ninterpreter network is able to generalize to real data. Our end-to-end system\nfor object pose estimation runs in real-time (20 Hz) on live RGB data, without\nusing depth information or ICP refinement.","url_abs":"http://arxiv.org/abs/1808.01099v1","url_pdf":"http://arxiv.org/pdf/1808.01099v1.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":"real-time-object-pose-estimation-with-pose","repo_url":"https://github.com/jimmyyhwu/pose-interpreter-networks","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"real-time-object-pose-estimation-with-pose","repo_url":"https://github.com/verityw/manipulation-final-project","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"object","task_name":"Object"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1808.01099","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}