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English(EN) GuideGround: VLM-guided Semantic Understanding and Viewpoint-aware Reasoning for 3D Visual Grounding

新框架通过LLM和VLM增强3D视觉定位 · 跟踪2个来源

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了两个新框架TDVR和GuideGround，以改进零样本3D视觉定位。TDVR通过使用LLM进行文本消歧和链式思考推理进行视角推断，解决了文本歧义和视角缺失的挑战。另一方面，GuideGround利用视觉语言模型（VLM）来增强语义理解并验证特定视角的假设。这两种方法在基准数据集上的表现都显著优于现有的最先进方法。 AI

影响 这些进步可能导致3D环境中更准确、更鲁棒的目标定位，影响机器人和增强现实等领域。

排序理由 两篇介绍3D视觉定位新方法的学术论文。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新框架通过LLM和VLM增强3D视觉定位 · 跟踪2个来源

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Research
两篇介绍3D视觉定位新方法的学术论文。
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2 independent sources
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Topics
paper, model release
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81 days old
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Qingxi Du, Junbo Wang, Yuke Li, Yining Zhu ·

    TDVR：联合文本消歧与视角推理实现零样本三维视觉定位

    arXiv:2608.03763v1 Announce Type: new Abstract: Zero-shot 3D visual grounding aims to localize specific objects based on textual descriptions and 3D visual input. However, the effectiveness of existing methods is significantly hindered by the ambiguous query text and deficient vi…

  2. arXiv cs.CV TIER_1 English(EN) · Yiwen Wang, Yuyang Deng, Yihao Long, Xi Zhao ·

    GuideGround：VLM引导的语义理解和视角感知推理用于3D视觉定位

    arXiv:2608.00518v1 Announce Type: new Abstract: 3D visual grounding aims to localize the target object in a 3D scene from a natural language query, requiring both fine-grained semantic understanding and viewpoint-dependent spatial reasoning. Existing methods typically formulate s…

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