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English(EN) DEQ-Stereo: Deep Euilibrium Video Stereo Matching via Adaptive Convergence

DEQ-Stereo 框架使用深度均衡模型进行自适应视频立体匹配

研究人员推出了一种新颖的视频立体匹配框架 DEQ-Stereo,该框架利用了深度均衡 (DEQ) 范式。这种方法将精炼过程重新表述为一个隐式不动点问题,允许在收敛时自适应终止,而不是依赖于固定数量的迭代。该框架包含一个卷积简化门控单元 (ConvSGU) 以实现高效的帧内收敛,以及时间状态传输 (TST) 以通过传播隐藏状态来利用帧间相干性。评估表明,DEQ-Stereo 在准确性与延迟的权衡方面取得了最先进的性能。 AI

影响 引入了一种新颖的视频立体匹配方法,提高了准确性并降低了延迟。

排序理由 该集群包含一篇详细介绍视频立体匹配新方法的 ist-of-research paper。 [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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DEQ-Stereo 框架使用深度均衡模型进行自适应视频立体匹配

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该集群包含一篇详细介绍视频立体匹配新方法的 ist-of-research paper。 [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) · Kiljoon Han, Kyumin Hwang, Wonhyeok Choi, Jeonghoon Kim, Sunghoom Im ·

    DEQ-Stereo:通过自适应收敛实现深度平衡视频立体匹配

    arXiv:2610.39701v2 Announce Type: replace Abstract: Iterative refinement models have significantly improved stereo matching accuracy, but their rigid, fixed update schedules incur heavy computational costs and a strict trade-off between speed and accuracy. This challenge is magni…