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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Model · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2211.16374/</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/2211.16374/feed.xml" rel="self" type="application/rss+xml" /><item><title>DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Model — mentioned by bradkim990</title><link>https://news.ycombinator.com/item?id=35452472</link><guid isPermaLink="false">urn:hackerpapers:mention:2211.16374:35452472</guid><pubDate>Wed, 05 Apr 2023 11:46:00 GMT</pubDate><description>&lt;p&gt;Hi HMs! Happy to share the Code &amp;amp; Gradio demo &amp;amp; Colab demo for our paper, &amp;quot;DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Model&amp;quot; (accepted to CVPR2023). We showcase the demo of text-guided manipulated 3D reconstuction (Single-shot Text-guided 2D-to-3D) of the portrait beyond text-guided image manipulation! - Paper: https://arxiv.org/abs/2211.16374 - Project: https://gwang-kim.github.io/datid_3d/ - Code &amp;amp; Colab &amp;amp; Gradio Demo: https://github.com/gwang-kim/DATID-3D DATID-3D succeeded in text-guided domain adaptation of 3D-aware generative models…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2211.16374/"&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>
