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English(EN) NegROI: Click-Centric Uncertainty-Guided Refinement with Scene-Conditioned Negative Prompts for Robust Interactive 3D Segmentation

NegROI框架通过负面提示改进3D分割

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员推出了一种名为NegROI的新型基于Transformer的框架，旨在增强交互式3D分割。该方法通过将以点击为中心的精炼与场景条件负面提示相结合，解决了体素分辨率粗糙和假阳性等挑战。NegROI仅精炼用户点击周围的局部感兴趣区域，并利用置信度驱动的选择性精炼来优先处理模糊区域，从而提高不同数据集的效率和鲁棒性。 AI

影响 这项研究可能带来更准确、更高效的3D对象提取，应用于机器人、增强现实等各种场景。

排序理由 该集群包含一篇详细介绍3D分割新方法的论文。

在 arXiv cs.AI 阅读 →

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NegROI框架通过负面提示改进3D分割

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该集群包含一篇详细介绍3D分割新方法的论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Shuheng Zhang, Feng Wu ·

    NegROI：以点击为中心的、由不确定性引导的、带有场景条件负面提示的精炼方法，用于鲁棒的交互式三维分割

    arXiv:2607.05955v1 Announce Type: cross Abstract: Interactive 3D segmentation aims to extract object masks in point clouds with minimal user clicks. Despite recent progress, most existing approaches still struggle with (i) coarse voxel resolution that blurs fine boundaries under …

  2. arXiv cs.AI TIER_1 English(EN) · Feng Wu ·

    NegROI：以点击为中心的、由场景条件负面提示引导的不确定性细化，用于鲁棒的交互式3D分割

    Interactive 3D segmentation aims to extract object masks in point clouds with minimal user clicks. Despite recent progress, most existing approaches still struggle with (i) coarse voxel resolution that blurs fine boundaries under limited clicks and (ii) hard false positives cause…

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