<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>3D on Yosgi</title><link>https://yosgi.github.io/en/tags/3d/</link><description>Recent content in 3D on Yosgi</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 29 Jun 2026 09:20:51 +0000</lastBuildDate><atom:link href="https://yosgi.github.io/en/tags/3d/index.xml" rel="self" type="application/rss+xml"/><item><title>Using AI Agents for Asset Recognition and Annotation in 3D Scenes (Part 3)</title><link>https://yosgi.github.io/en/post/using-ai-agents-for-asset-recognition-and-annotation-in-3d-scenes-part-3/</link><pubDate>Sun, 21 Jun 2026 10:00:00 +1200</pubDate><guid>https://yosgi.github.io/en/post/using-ai-agents-for-asset-recognition-and-annotation-in-3d-scenes-part-3/</guid><description>Making scan results land in the right place</description></item><item><title>Using AI Agents for Asset Recognition and Annotation in 3D Scenes (Part 2)</title><link>https://yosgi.github.io/en/post/using-ai-agents-for-asset-recognition-and-annotation-in-3d-scenes-part-2/</link><pubDate>Sat, 20 Jun 2026 19:11:11 +1200</pubDate><guid>https://yosgi.github.io/en/post/using-ai-agents-for-asset-recognition-and-annotation-in-3d-scenes-part-2/</guid><description>How we split 2D detection and 3D verification into two stages to reduce false positives in digital twin asset annotation, and how that revealed the next recall bottleneck</description></item><item><title>Using AI Agents for Asset Recognition and Annotation in 3D Scenes</title><link>https://yosgi.github.io/en/post/using-ai-agents-for-asset-recognition-and-annotation-in-3d-scenes-part-1/</link><pubDate>Fri, 19 Jun 2026 09:46:11 +1200</pubDate><guid>https://yosgi.github.io/en/post/using-ai-agents-for-asset-recognition-and-annotation-in-3d-scenes-part-1/</guid><description>How we turned free-form 3D exploration into measurable coverage scanning and improved valve inventory recall in a digital twin factory from around 40% to around 90%</description></item><item><title>From Extracting Drawing Text to Placing 2D Annotations in a 3D Scene</title><link>https://yosgi.github.io/en/post/from-extracting-drawing-text-to-placing-2d-annotations-in-a-3d-scene/</link><pubDate>Fri, 12 Jun 2026 11:28:21 +1200</pubDate><guid>https://yosgi.github.io/en/post/from-extracting-drawing-text-to-placing-2d-annotations-in-a-3d-scene/</guid><description>A practical engineering recap of how a simple drawing text extraction task turned into a 2D-to-3D mapping workflow for digital twins, combining SVG parsing, vision models, geometry rules, registration math, and agent tool design.</description></item><item><title>High-Frequency Synchronization Architecture Between React State and a 3D Engine</title><link>https://yosgi.github.io/en/post/high-frequency-synchronization-architecture-between-react-state-and-a-3d-engine/</link><pubDate>Sat, 31 Jan 2026 23:42:31 +1300</pubDate><guid>https://yosgi.github.io/en/post/high-frequency-synchronization-architecture-between-react-state-and-a-3d-engine/</guid><description>A synchronization paradigm for massive real-time data: a middle layer isolates high-frequency data sources, and React consumes only the linear projection of the visible viewport.</description></item></channel></rss>