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English(EN) A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$

新框架将视觉 Transformer 与离散对称性统一起来

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种新的视觉 Transformer 框架，该框架融入了离散对称性，特别是 O(2) 的子群。这种方法推广了现有的等变 Transformer 架构，并为所得层的表达能力提供了理论保证。在 PatternNet 数据集上的实验表明，融入等变性可以提高识别精度，尤其是在数据稀缺的情况下，这促使人们进一步研究离散对称群在视觉识别模型中的作用。 AI

影响 这项研究通过利用图像数据中固有的对称性，有可能带来更准确、更具数据效率的视觉识别模型。

排序理由 该集群包含一篇详细介绍视觉 Transformer 新框架的学术论文。

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新框架将视觉 Transformer 与离散对称性统一起来

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该集群包含一篇详细介绍视觉 Transformer 新框架的学术论文。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · T\={\i}kun \^Ong, Georg B\"okman ·

    用于离散 O(2) 子群的视觉 Transformer 的统一框架

    arXiv:2606.27864v1 Announce Type: cross Abstract: Vision transformers have become a dominant architecture for visual recognition. However, standard models do not explicitly encode the planar symmetries that arise in many vision domains. We introduce a family of vision transformer…

  2. arXiv cs.LG TIER_1 English(EN) · Georg Bökman ·

    用于离散 O(2) 子群的视觉 Transformer 的统一框架

    Vision transformers have become a dominant architecture for visual recognition. However, standard models do not explicitly encode the planar symmetries that arise in many vision domains. We introduce a family of vision transformers equivariant to arbitrary discrete subgroups of $…

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