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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Handcrafted Local Features are Convolutional Neural Networks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1511.05045/</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/1511.05045/feed.xml" rel="self" type="application/rss+xml" /><item><title>Handcrafted Local Features are Convolutional Neural Networks — mentioned by Sergej-Shegurin</title><link>https://news.ycombinator.com/item?id=11283693</link><guid isPermaLink="false">urn:hackerpapers:mention:1511.05045:11283693</guid><pubDate>Mon, 14 Mar 2016 16:19:13 GMT</pubDate><description>&lt;p&gt;(1) Adversarial learning is unsupervised and works great. Most of language modeling is unsupervised (you predict next word, but it&amp;#x27;s not real supervision because it&amp;#x27;s self-supervision). There&amp;#x27;re many works in computer vision which are unsupervised and still give more or less reasonable performance. See f.e. http://arxiv.org/pdf/1511.05045v2.pdf for unsupervised learning in action recognition, also http://arxiv.org/pdf/1511.06434v2.pdf and http://www.arxiv-sanity.com/search?q=unsupervised (2) ImageNet supervision gives you much information to solve other computer vision tasks. So perhaps we…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1511.05045/"&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>
