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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1612.00593/</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/1612.00593/feed.xml" rel="self" type="application/rss+xml" /><item><title>PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation — mentioned by gaudetcj</title><link>https://news.ycombinator.com/item?id=16657682</link><guid isPermaLink="false">urn:hackerpapers:mention:1612.00593:16657682</guid><pubDate>Fri, 23 Mar 2018 13:13:46 GMT</pubDate><description>&lt;p&gt;This paper was mostly to lay out the framework and give out the Keras layers for others to use. We expect that the biggest improvements will come from segmentation where the gains may come from treating each color channel as an imaginary axis. And from architectures like PointNet https://arxiv.org/abs/1612.00593.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1612.00593/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
