<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>3D-Reconstruction on Xu'Blog</title><link>https://xuquant.com/tags/3d-reconstruction/</link><description>Recent content in 3D-Reconstruction on Xu'Blog</description><image><title>Xu'Blog</title><url>https://xuquant.com/og-default.png</url><link>https://xuquant.com/og-default.png</link></image><generator>Hugo -- 0.152.2</generator><language>zh</language><lastBuildDate>Sat, 21 Mar 2026 18:00:00 +0800</lastBuildDate><atom:link href="https://xuquant.com/tags/3d-reconstruction/index.xml" rel="self" type="application/rss+xml"/><item><title>SceneVerse++: Lifting Unlabeled Internet Videos into 3D Scene Understanding Training Data</title><link>https://xuquant.com/posts/foundation-models/sceneverse-plus-data-engine-for-3d-scene-understanding/</link><pubDate>Sat, 21 Mar 2026 18:00:00 +0800</pubDate><guid>https://xuquant.com/posts/foundation-models/sceneverse-plus-data-engine-for-3d-scene-understanding/</guid><description>Deep analysis of CVPR 2026 SceneVerse++: how to build the largest-scale real-world 3D scene dataset from unlabeled internet videos, covering detection, segmentation, spatial VQA, and vision-language navigation.</description></item><item><title>VGGT: 几何重建作为世界模型的 reconstruct 维度</title><link>https://xuquant.com/posts/world-models/vggt/</link><pubDate>Sat, 21 Mar 2026 10:00:00 +0800</pubDate><guid>https://xuquant.com/posts/world-models/vggt/</guid><description>VGGT 把多视图 3D 重建压缩为单次前向传播。本文重新核对 alternating attention 的复杂度推导、用 VGGT 论文 Table 3/5/6 的原始数字检验过完备预测策略，并从几何先验转移与表示哲学两个角度回答：为什么从深度与位姿组合出的点图反而比直接预测更准。</description></item><item><title>Depth Anything 3: Geometric Grounding for World Models</title><link>https://xuquant.com/posts/world-models/depth-anything-3/</link><pubDate>Sat, 07 Feb 2026 10:00:00 +0800</pubDate><guid>https://xuquant.com/posts/world-models/depth-anything-3/</guid><description>Depth Anything 3 unifies monocular depth, multi-view reconstruction, pose estimation, and novel view synthesis under a single depth-ray representation. This article analyzes why minimal representation matters for world models and what depth estimation reveals about the geometric foundations of physical understanding.</description></item></channel></rss>