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English(EN) UniPart: Towards Zero-shot Language-Grounded 3D Part Segmentation for Embodied Interaction

UniPart 引入零样本语言基础3D部件分割

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员引入了UniPart，一种新颖的前馈跨模态3D Transformer，专为零样本语言基础3D部件分割而设计。该模型旨在克服现有3D基础模型的局限性，通过实现具有开放词汇迁移能力的部件感知分割。UniPart以CLIP文本嵌入为条件，并使用LangPart-1M数据集进行训练，该数据集包含超过16万个Objaverse资产和800万个文本到部件对。该系统在部件分割基准测试中表现出强大的零样本性能，并已成功应用于现实场景中的语言条件部件抓取。 AI

影响 这项研究通过实现精确的、语言引导的对象部件识别，可以实现更复杂的机器人操作和交互。

排序理由 该集群描述了一篇关于用于3D部件分割的新型模型和数据集的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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UniPart 引入零样本语言基础3D部件分割

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该集群描述了一篇关于用于3D部件分割的新型模型和数据集的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xinqiang Yu, Zekun qi, Jiawei He, Wenyao Zhang, Xuchuan Chen, Guaocai Yao, Li Yi, Zhaoxiang Zhang, He Wang ·

    UniPart：迈向面向具身交互的零样本语言引导式三维部件分割

    arXiv:2609.12898v1 Announce Type: new Abstract: Fine-grained robotic manipulation depends on understanding parts, not only whole objects. Existing 3D foundation models tend to be either generalized but object-aware, or part-aware but limited to closed-set taxonomies, which weaken…

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