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English(EN) Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM

新型LMM支持感知度量的3D空间推理和地面定位

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出Ground3D-LMM，这是一种旨在增强3D环境自然语言理解的新型模型。该模型通过提供明确关联到特定3D区域并包含真实世界单位度量衡的响应，支持关于3D空间的交互式对话。为此，定义了一个名为3D Grounded Measurement的新任务，以及一个包含约250万个问答对、源自ScanNet和ScanNet++的大规模数据集。 AI

影响 该模型能够实现更精确和交互式的AI应用，用于理解和操作3D环境，对机器人和增强现实等领域产生影响。

排序理由 该集群描述了一篇介绍用于3D空间推理的新型模型和数据集的研究论文。[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 →

新型LMM支持感知度量的3D空间推理和地面定位

本文如何被排名

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该集群描述了一篇介绍用于3D空间推理的新型模型和数据集的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Amol Harsh, Zongyan Han, Jean Lahoud, Ye Liu, Rao Muhammad Anwer, Hisham Cholakkal, Salman Khan, Fahad Khan ·

    Ground3D-LMM：具有LMM的细粒度3D点地面定位和空间推理

    arXiv:2607.05493v1 Announce Type: new Abstract: Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to the referred 3D region, while metric answers report physical measurements in rea…

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