English(EN) STATIC: Surface-normal-guided Two-branch Alignment and Temporal Integration for Consistent Video Depth Estimation

新的STATIC模型通过帧间一致性增强视频深度估计

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-26 04:00

研究人员开发了STATIC，一种用于视频深度估计的新型模型，可提高帧间的时间一致性。与依赖外部运动先验的先前方法不同，STATIC仅使用两个相邻帧独立学习稳定和不稳定区域的一致性。它利用表面法线创建了一个几何感知的差异掩码，通过掩码稳定模块增强稳定区域，并通过表面法线相似性模块增强不稳定区域。在KITTI、NYUv2和Sintel数据集上的实验表明，STATIC在深度准确性和时间一致性方面表现出色，在各种帧率和相机运动下均表现稳健。 AI

影响提高了视频深度估计中的时间一致性，可能使自动驾驶和机器人等应用受益。

排序理由该集群描述了一篇详细介绍视频深度估计新模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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本文如何被排名

Signal score: 17 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群描述了一篇详细介绍视频深度估计新模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Sunghun Yang, Minhyeok Lee, Suhwan Cho, Jungho Lee, Sangyoun Lee · 2026-10-26 04:00

STATIC：表面法线引导的双分支对齐与时间积分用于一致性视频深度估计

arXiv:2412.01090v3 Announce Type: replace Abstract: Video depth estimation is essential for applications such as autonomous driving, AR/VR, and robotics. Recent transformer-based single-image monocular depth estimation models perform well on a single image but struggle with depth…

本文如何被排名

报道来源 [1]

STATIC：表面法线引导的双分支对齐与时间积分用于一致性视频深度估计

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