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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Simple Open-Vocabulary Object Detection with Vision Transformers · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2205.06230/</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/2205.06230/feed.xml" rel="self" type="application/rss+xml" /><item><title>Simple Open-Vocabulary Object Detection with Vision Transformers — HN submission</title><link>https://news.ycombinator.com/item?id=33056317</link><guid isPermaLink="false">urn:hackerpapers:submission:2205.06230:33056317</guid><pubDate>Sun, 02 Oct 2022 14:48:49 GMT</pubDate><description>&lt;p&gt;Show HN: Zero-shot object detection demo&lt;/p&gt;&lt;p&gt;Hello HN! We&amp;#x27;ve built an interactive demo of Google AI&amp;#x27;s OWL-ViT [1] zero-shot object detection model, using Hugging Face transformers. Regular object detection models are trained on a fixed set of categories, for example cats, dogs and birds. If you want to detect a new type of object, like a horse, you have to collect and label images with horses and retrain your model. A zero-shot object detection model is a so-called open-vocabulary model: it can detect a huge number of object categories without needing to retrain it. These categories are not predefined: you can provide any free-form text…&lt;/p&gt;&lt;p&gt;3 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2205.06230/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>Simple Open-Vocabulary Object Detection with Vision Transformers — HN submission</title><link>https://news.ycombinator.com/item?id=32368088</link><guid isPermaLink="false">urn:hackerpapers:submission:2205.06230:32368088</guid><pubDate>Sat, 06 Aug 2022 13:52:59 GMT</pubDate><description>&lt;p&gt;Simple Open-Vocabulary Object Detection with Vision Transformers&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2205.06230/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
