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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Denoising Vision Transformers · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2401.02957/</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/2401.02957/feed.xml" rel="self" type="application/rss+xml" /><item><title>Denoising Vision Transformers — mentioned by radq</title><link>https://news.ycombinator.com/item?id=39761525</link><guid isPermaLink="false">urn:hackerpapers:mention:2401.02957:39761525</guid><pubDate>Tue, 19 Mar 2024 23:46:24 GMT</pubDate><description>&lt;p&gt;The training technique used here (fitting something similar to a NeRF to different views of the same image) is pretty similar to this paper which uses a similar technique to denoise (instead of upscale) output features: https://arxiv.org/abs/2401.02957&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2401.02957/"&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>
