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English(EN) Video Depth Anything: Consistent Depth Estimation for Super-Long Videos

Video Depth Anything 改进了长视频的深度估计

研究人员开发了 Video Depth Anything,一种用于超长视频一致性深度估计的新颖方法。该新方法基于 Depth Anything V2 模型,并结合了高效的时空头和时间深度梯度损失,可在不依赖外部几何先验的情况下保持一致性。该方法专为超过数分钟的视频设计,在零样本视频深度估计方面展现了最先进的性能,并提供了可实现实时性能的模型。 AI

影响 增强了深度估计在长篇视频内容中的实际应用。

排序理由 详细介绍视频深度估计新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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Video Depth Anything 改进了长视频的深度估计

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详细介绍视频深度估计新方法的学术论文。[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) · Sili Chen, Hengkai Guo, Shengnan Zhu, Feihu Zhang, Zilong Huang, Jiashi Feng, Bingyi Kang ·

    Video Depth Anything: 超长视频的一致性深度估计

    arXiv:2501.12375v4 Announce Type: replace Abstract: Depth Anything has achieved remarkable success in monocular depth estimation with strong generalization ability. However, it suffers from temporal inconsistency in videos, hindering its practical applications. Various methods ha…