<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Deep Learning-based Face Super-Resolution: A Survey · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2101.03749/</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/2101.03749/feed.xml" rel="self" type="application/rss+xml" /><item><title>Deep Learning-based Face Super-Resolution: A Survey — mentioned by russdill</title><link>https://news.ycombinator.com/item?id=36312053</link><guid isPermaLink="false">urn:hackerpapers:mention:2101.03749:36312053</guid><pubDate>Tue, 13 Jun 2023 15:50:27 GMT</pubDate><description>&lt;p&gt;You linked to an actual imaging technique called super-resolution imaging which is for imaging. It&amp;#x27;s a technique applied to the capture of an image, and cannot be applied to an already captured image. Machine learning super resolution adds detail to image that does not exist, in the same way that image inpainting (or even outpainting) do. https://arstechnica.com/information-technology/2017/02/googl... &amp;quot;It&amp;#x27;s important to note that the computed super-resolution image is not real. The added details—known as &amp;quot;hallucinations&amp;quot; in image processing jargon—are a best guess and nothing more.&amp;quot; If you go…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2101.03749/"&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>
