We propose Gated Stereo, a high-resolution and long-range depth estimation technique that operates on active gated stereo images. Using active and high dynamic range passive captures, Gated Stereo exploits multi-view cues alongside time-of-flight intensity cues from active gating. To this end, we propose a depth estimation method with a monocular and stereo depth prediction branch which are combined in a final fusion stage. Each block is supervised through a combination of supervised and gated self-supervision losses. To facilitate training and validation, we acquire a long-range synchronized gated stereo dataset for automotive scenarios. We find that the method achieves an improvement of more than 50 % MAE compared to the next best RGB stereo method, and 74 % MAE to existing monocular gated methods for distances up to 160 m. Our code,models and datasets are available here.

该研究提出了一种基于主动门控立体图像的高分辨率和长距离深度估计技术-Gated Stereo，该技术利用主动和高动态范围的被动捕获，利用多视图线索以及来自主动门控的飞行时间强度线索。其中，该研究提出了一种通过单目和立体深度预测分支组合的深度估计方法，并且每个块都通过监督和门控自监督损失进行监督, 并为汽车场景获取了一种长距离同步门控立体数据集。该方法的性能比最佳RGB立体方法提高了50％以上的MAE，并比现有的单目门控方法在距离160米内的距离范围内提供了74％的MAE。

门控立体：基于门控和宽基线主动立体线索的联合深度估计