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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1612.01887/</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/1612.01887/feed.xml" rel="self" type="application/rss+xml" /><item><title>Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning — mentioned by Smerity</title><link>https://news.ycombinator.com/item?id=14356931</link><guid isPermaLink="false">urn:hackerpapers:mention:1612.01887:14356931</guid><pubDate>Wed, 17 May 2017 09:49:16 GMT</pubDate><description>&lt;p&gt;This is all doable today. As an example, check out some bird photos[1] from the Visual Genome[2] project that are similar to your examples. I selected the photos and hosted them on Imgur in hopes we don&amp;#x27;t kill Visual Genome with traffic ;) The systems to do this today are not highly efficient or without flaws but it can certainly be done. The research group I am part of, Salesforce Research (formerly MetaMind), have a model that does this &amp;quot;accidentally&amp;quot; - and there&amp;#x27;s even an example image of a bird[3]! The model is only meant to provide a caption for an image, not to segment the image into…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1612.01887/"&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>
