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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Towards synthesizing grasps for 3D deformable objects with physics-based simulation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2107.08898/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2107.08898/feed.xml" rel="self" type="application/rss+xml" /><item><title>Towards synthesizing grasps for 3D deformable objects with physics-based simulation — mentioned by zone411</title><link>https://news.ycombinator.com/item?id=33636542</link><guid isPermaLink="false">urn:hackerpapers:mention:2107.08898:33636542</guid><pubDate>Thu, 17 Nov 2022 09:06:45 GMT</pubDate><description>&lt;p&gt;This has been a thing for a while. For example, here are a couple random papers from 2017: https://openaccess.thecvf.com/content_cvpr_2017/html/Varol_L..., https://openaccess.thecvf.com/content_ICCV_2017_workshops/w2... or a newer one about deformable objects: https://arxiv.org/abs/2107.08898. You can even use a robot to manipulate things in real life to create synthetic data for a neural net.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2107.08898/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.RO</category></item></channel></rss>
