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English(EN) EmbPASS: Towards Cross-Embodiment Open Panoramic Segmentation

新基准和模型应对跨具身全景分割

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员引入了一项名为跨具身开放全景分割的新任务，以解决不同具身平台之间一致场景理解的挑战。他们还建立了EmbPASS，这是一个包含车辆、无人机、可穿戴设备和四足平台语义分割的基准数据集。为了解决这个问题，他们提出了EPONet，一个旨在改善异构具身观测的空间建模和语义迁移的网络，在EmbPASS基准上实现了35.82%的平台平衡mIoU。 AI

影响 这项研究可能为在多样化环境中运行的机器人和自主平台的更强大、更适应性强的人工智能系统铺平道路。

排序理由 该集群描述了一篇介绍计算机视觉新任务、新基准和新模型的新学术论文。[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 →

新基准和模型应对跨具身全景分割

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该集群描述了一篇介绍计算机视觉新任务、新基准和新模型的新学术论文。[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) · Pujun Guo, Yuanfan Zheng, Fei Teng, Mengfei Duan, Guoqiang Zhao, Yuheng Zhang, Kai Luo, Kailun Yang ·

    EmbPASS：迈向跨具身全景开放分割

    arXiv:2610.03248v1 Announce Type: new Abstract: Panoramic images provide a complete 360-degree field of view, enabling comprehensive scene understanding for embodied perception. However, heterogeneous embodied platforms exhibit substantial differences in observation viewpoints an…

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