{"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/learning-gradient-fields-for-shape-generation","title":"Learning Gradient Fields for Shape Generation","arxiv_id":"2008.06520","date":"2020-08-14","proceeding":"ECCV 2020 8","authors":["Ruojin Cai","Guandao Yang","Hadar Averbuch-Elor","Zekun Hao","Serge Belongie","Noah Snavely","Bharath Hariharan"],"abstract":"In this work, we propose a novel technique to generate shapes from point cloud data. A point cloud can be viewed as samples from a distribution of 3D points whose density is concentrated near the surface of the shape. 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