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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1609.05158/</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/1609.05158/feed.xml" rel="self" type="application/rss+xml" /><item><title>Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network — mentioned by akarve</title><link>https://news.ycombinator.com/item?id=17579888</link><guid isPermaLink="false">urn:hackerpapers:mention:1609.05158:17579888</guid><pubDate>Fri, 20 Jul 2018 23:48:58 GMT</pubDate><description>&lt;p&gt;Quilt isn&amp;#x27;t doing the inference (the PyTorch model is). But, in any case, no. Super-resolution is more than blurring, it&amp;#x27;s pixel inference. https://arxiv.org/abs/1609.05158&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1609.05158/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network — mentioned by trustswz</title><link>https://news.ycombinator.com/item?id=12620352</link><guid isPermaLink="false">urn:hackerpapers:mention:1609.05158:12620352</guid><pubDate>Sat, 01 Oct 2016 23:21:11 GMT</pubDate><description>&lt;p&gt;If you are interested in how it compares to bicubic or the original. Check these papers using the sub pixel convolutional layer: https://arxiv.org/abs/1609.05158 https://arxiv.org/abs/1609.04802.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1609.05158/"&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>
