English(EN) A Vision-Language Model (VLM)-based Pipeline for End-to-End Procedural Modeling of Field-Grown Maize from Point Clouds

视觉语言模型自动化3D玉米植株重建

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-05 04:00

研究人员开发了一种新颖的管线，该管线使用视觉语言模型（VLM）从点云数据中自动生成可编辑的田间玉米植株3D模型。该系统在渲染视图中注释叶片中线，然后用于重建3D叶片并将其生长成完整的叶片。该管线填充了基于非均匀有理B样条（NURBS）的程序化模型生成器的描述符，并根据扫描点精炼每个叶片表面。该方法实现了5.4毫米的植株整体Chamfer距离中位数，优于先前的手动辅助管线，并证明了用于表型分析实验的大规模、自动化3D植物资产生成的可能性。 AI

影响能够大规模、自动化地生成可编辑的3D植物资产，用于农业研究和育种。

排序理由该项目是一篇学术论文，详细介绍了一种使用AI进行3D建模的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Mozhgan Hadadi, Talukder Z. Jubery, Adarsh Krishnamurthy, Baskar Ganapathysubramanian · 2026-10-05 04:00

一种基于视觉语言模型（VLM）的端到端程序化建模管线，用于从点云生成田间玉米

arXiv:2610.03468v1 Announce Type: new Abstract: Editable 3D models of field-grown crops support high-throughput phenotyping and in silico breeding trials, but building them from scanned point clouds requires organ-level segmentation and fitting. Procedural generators can turn an …

本文如何被排名

报道来源 [1]

一种基于视觉语言模型（VLM）的端到端程序化建模管线，用于从点云生成田间玉米

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