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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Adversarial examples in the physical world · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1607.02533/</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/1607.02533/feed.xml" rel="self" type="application/rss+xml" /><item><title>Adversarial examples in the physical world — mentioned by dijksterhuis</title><link>https://news.ycombinator.com/item?id=23922479</link><guid isPermaLink="false">urn:hackerpapers:mention:1607.02533:23922479</guid><pubDate>Wed, 22 Jul 2020 22:58:25 GMT</pubDate><description>&lt;p&gt;This can be thwarted fairly easily https://arxiv.org/pdf/1607.02533.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1607.02533/"&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>Adversarial examples in the physical world — HN submission</title><link>https://news.ycombinator.com/item?id=20970636</link><guid isPermaLink="false">urn:hackerpapers:submission:1607.02533:20970636</guid><pubDate>Sat, 14 Sep 2019 13:28:36 GMT</pubDate><description>&lt;p&gt;Adverserial Examples in the Physical World&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1607.02533/"&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>Adversarial examples in the physical world — mentioned by anishathalye</title><link>https://news.ycombinator.com/item?id=15613701</link><guid isPermaLink="false">urn:hackerpapers:mention:1607.02533:15613701</guid><pubDate>Thu, 02 Nov 2017 19:58:25 GMT</pubDate><description>&lt;p&gt;Goodfellow et al. demonstrate that adversarial misclassification works in the physical world: https://arxiv.org/abs/1607.02533 -- a printed image is consistently misclassified (demo here: https://www.youtube.com/watch?v=zQ_uMenoBCk) Recent work by me and some friends demonstrates that physical-world adversarial examples can actually be made quite robust, and you can synthesize 3D adversarial objects as well, and make them consistently classify as a desired target class: http://www.labsix.org/physical-objects-that-fool-neural-nets...&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1607.02533/"&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>Adversarial examples in the physical world — HN submission</title><link>https://news.ycombinator.com/item?id=12206704</link><guid isPermaLink="false">urn:hackerpapers:submission:1607.02533:12206704</guid><pubDate>Mon, 01 Aug 2016 22:57:10 GMT</pubDate><description>&lt;p&gt;Adversarial examples in the physical world&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/1607.02533/"&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>Adversarial examples in the physical world — HN submission</title><link>https://news.ycombinator.com/item?id=12158573</link><guid isPermaLink="false">urn:hackerpapers:submission:1607.02533:12158573</guid><pubDate>Mon, 25 Jul 2016 13:39:01 GMT</pubDate><description>&lt;p&gt;Fooling machine learning image classifier&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/1607.02533/"&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>Adversarial examples in the physical world — mentioned by danielmorozoff</title><link>https://news.ycombinator.com/item?id=12151228</link><guid isPermaLink="false">urn:hackerpapers:mention:1607.02533:12151228</guid><pubDate>Sat, 23 Jul 2016 22:16:39 GMT</pubDate><description>&lt;p&gt;link to the paper. http://arxiv.org/abs/1607.02533 Their method more maximizing the cross entropy yields very peculiar results if you look at the images as the hyper-parameter iterations go up. It seems as if what we are seeing is some convolution with some peculiar form of noise. I wonder what the structure across these adversarial images looks like and whether it could provide some insight into certain patterns in cov net learning?&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1607.02533/"&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>Adversarial examples in the physical world — HN submission</title><link>https://news.ycombinator.com/item?id=12097304</link><guid isPermaLink="false">urn:hackerpapers:submission:1607.02533:12097304</guid><pubDate>Thu, 14 Jul 2016 21:28:54 GMT</pubDate><description>&lt;p&gt;Adversarial Examples in the Real World&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/1607.02533/"&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>Adversarial examples in the physical world — HN submission</title><link>https://news.ycombinator.com/item?id=12087684</link><guid isPermaLink="false">urn:hackerpapers:submission:1607.02533:12087684</guid><pubDate>Wed, 13 Jul 2016 16:54:56 GMT</pubDate><description>&lt;p&gt;Adversarial examples in the physical world&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;3 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1607.02533/"&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>
