English(EN) VGGT-Bridge: Beyond Sequential Pose Graphs via Coarse-Stride Skip Edges

VGGT-Bridge 通过远程跳跃边提高 3D 重建精度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-23 04:00

研究人员开发了 VGGT-Bridge，一种改进视觉几何变换器 (VGGTs) 从图像重建 3D 结构精度的新方法。现有的 VGGTs 由于二次注意力复杂度，在处理长序列时遇到困难，导致累积漂移。VGGT-Bridge 通过引入连接非相邻序列块的远程跳跃边来解决此问题，直接约束它们并减少漂移。该方法在 KITTI Odometry 等基准数据集上显示出显著改进，绝对轨迹误差最多可降低 28.3%。 AI

影响提高了从图像进行 3D 重建的精度和可扩展性，可能为机器人和自动驾驶领域提供更强大的应用。

排序理由这是一篇详细介绍改进现有计算机视觉模型的新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Sungjae Choi, Hanna Bae, Sunghyun Baek, Junmo Kim · 2026-10-23 04:00

VGGT-Bridge: Beyond Sequential Pose Graphs via Coarse-Stride Skip Edges

arXiv:2610.06594v2 Announce Type: replace Abstract: Feed-forward visual geometry transformers such as VGGT reconstruct dense 3D structure from images in a single forward pass, simplifying multi-view 3D reconstruction. However, their quadratic attention complexity makes them diffi…

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VGGT-Bridge: Beyond Sequential Pose Graphs via Coarse-Stride Skip Edges

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