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English(EN) Learning Instance-Adaptive Low-Rank Orthogonal Subspaces for Clothes-Changing Person Re-Identification

研究人员开发出应对服装变换的行人重识别新方法

作者 PulseAugur 编辑部 · [2 个来源] ·

两篇新研究论文解决了服装变换行人重识别（CC-ReID）的挑战，即在个体衣着发生变化时仍能识别出他们。第一篇论文Ortho-ReID提出了一种基于Transformer的方法，通过几何约束来建模低秩服装子空间并提取服装不变的表示。第二篇论文Causal Clothes-Invariant Learning（CCIL）提出了一种基于因果关系的方法，以防止模型学习到服装与身份之间的虚假关联，从而提高对未见服装的泛化能力。 AI

影响 这些论文通过解决服装变化带来的挑战，推进了行人重识别技术，有望改进监控和安全系统。

排序理由 两篇在arXiv上发表的学术论文，提出了计算机视觉任务的新方法。

在 arXiv cs.LG 阅读 →

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研究人员开发出应对服装变换的行人重识别新方法

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两篇在arXiv上发表的学术论文，提出了计算机视觉任务的新方法。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Dong-Woo Kim, Tae-Kyun Kim ·

    面向服装变换行人重识别的学习实例自适应低秩正交子空间

    arXiv:2606.11661v1 Announce Type: cross Abstract: Clothes-changing person re-identification (CC-ReID) aims to recognize individuals despite drastic appearance changes caused by clothing variation. While existing methods rely on adversarial learning to disentangle clothing feature…

  2. arXiv cs.CV TIER_1 English(EN) · Xulin Li, Yan Lu, Bin Liu, Jiaze Li, Yating Liu, Qi Chu, Mang Ye, Wanli Ouyang, Nenghai Yu ·

    用于服装变化行人重识别的因果服装不变特征学习

    arXiv:2305.06145v2 Announce Type: replace Abstract: In cloth-changing person re-identification (CCReID), it is critical to learn clothes-invariant feature, which can provide discriminative ID features that remain robust against clothing changes. However, a spurious correlation cu…

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