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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Detecting Deep-Fake Videos from Appearance and Behavior · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2004.14491/</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/2004.14491/feed.xml" rel="self" type="application/rss+xml" /><item><title>Detecting Deep-Fake Videos from Appearance and Behavior — mentioned by kortex</title><link>https://news.ycombinator.com/item?id=32389320</link><guid isPermaLink="false">urn:hackerpapers:mention:2004.14491:32389320</guid><pubDate>Mon, 08 Aug 2022 18:43:17 GMT</pubDate><description>&lt;p&gt;It&amp;#x27;s a constant cat-and-mouse game. When I worked in this space (2019-2021), the best defense against deep fakes was looking at the microfacial behavior/kinematics of the &amp;quot;puppetmaster&amp;quot; and comparing against known standards of the deepfake subject. Works even if the fake is pixel-perfect (since it looks at the facial &amp;quot;wireframe&amp;quot; rather than the image itself). The obvious downside is you need sample data of the subject (and usually tons of it). I wonder if that general approach can be optimized. E.g. Deep fakes tend to struggle with certain fine movement/detail, if you had a reflection of the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2004.14491/"&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>Detecting Deep-Fake Videos from Appearance and Behavior — mentioned by kortex</title><link>https://news.ycombinator.com/item?id=32389195</link><guid isPermaLink="false">urn:hackerpapers:mention:2004.14491:32389195</guid><pubDate>Mon, 08 Aug 2022 18:32:47 GMT</pubDate><description>&lt;p&gt;Media forensics algorithms do work on various forms of rebroadcast, transmission, and compression, so yes this should be possible (for now). look up darpa medifor project. Siwei Lyu (in the article) did a bunch of work in this space. Also see Hany Farid and Shruti Agarwal. They&amp;#x27;ve worked specifically with deep fake detection. https://arxiv.org/abs/2004.14491&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2004.14491/"&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>
