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English(EN) IIT Patna at "ICPR 2026 TVRID Competition on Privacy-Preserving Person Re-Identification from Top-View RGB-Depth Camera"

IIT Patna 团队在隐私保护行人重识别竞赛中表现出色

印度理工学院 Patna 的研究人员展示了他们为 ICPR 2026 TVRID 隐私保护行人重识别竞赛提出的方法。他们的方法侧重于使用 RGB 和深度相机流来识别个体,同时最大限度地减少基于颜色的身份线索。IIT Patna 的两个团队进入了前十名,其中一个团队在深度赛道上取得了 93.51% 的 mAP 和 90.42% 的 CMC@1,显著优于平均水平。 AI

影响 展示了使用深度数据进行行人重识别的隐私保护技术的进步。

排序理由 该条目是一篇学术论文,详细介绍了竞赛的方法和结果。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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IIT Patna 团队在隐私保护行人重识别竞赛中表现出色

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该条目是一篇学术论文,详细介绍了竞赛的方法和结果。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Abhinav Kumar, Swagatam Pati, Advait Deshmukh, Aditya Mehrotra, Bibek Das, Kumari Priya, Utsav Kumar Nareti, Saba Akram, Chandranath Adak ·

    IIT Patna 荣获 "ICPR 2026 隐私保护顶视 RGB-深度相机人物重识别竞赛" 奖项

    arXiv:2611.12960v1 Announce Type: new Abstract: Privacy-aware person re-identification (Re-ID) from top-view cameras replaces frontal appearance with anthropometric shape, while depth sensing further reduces color-based identity cues. The ICPR 2026 TVRID competition evaluates thi…