English(EN) Leveraging Metric Depth for Relative Depth Prediction

新方法使用预训练模型预测相对深度

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-09 09:29

研究人员开发了一种新颖的方法，用于单目图像中的相对深度预测，特别是在足球场景下。他们的方法利用了大型预训练模型的零样本能力来推断度量深度，这有助于更准确的相对深度估计。该技术应用于2025 SoccerNet单目深度估计竞赛挑战，在挑战集上取得了2.68 x 10^-3的分数。 AI

影响该方法可以改进专业视觉领域的深度估计，有助于体育分析和增强现实等应用。

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arXiv cs.CV TIER_1 English(EN) · Xiaoyang Bi, Shuaikun Liu, Zhaohong Liu, Yuxin Yang, Zhe Zhao, Mengshi Qi, Liang Liu, Huadong Ma · 2026-06-10 04:00

利用度量深度进行相对深度预测

arXiv:2606.10628v1 Announce Type: new Abstract: We present our solution to the 2025 SoccerNet Monocular Depth Estimation Competition Challenge. Predicting the relative depth in football scenarios is challenging, especially with only thousands of training samples available. To add…
arXiv cs.CV TIER_1 English(EN) · Huadong Ma · 2026-06-09 09:29

利用度量深度进行相对深度预测

We present our solution to the 2025 SoccerNet Monocular Depth Estimation Competition Challenge. Predicting the relative depth in football scenarios is challenging, especially with only thousands of training samples available. To address this issue, our method leverages the powerf…