We present LightStereo, a cutting-edge stereo-matching network crafted to
accelerate the matching process. Departing from conventional methodologies that
rely on aggregating computationally intensive 4D costs, LightStereo adopts the
3D cost volume as a lightweight alternative. While similar approaches have been
explored previously, our breakthrough lies in enhancing performance through a
dedicated focus on the channel dimension of the 3D cost volume, where the
distribution of matching costs is encapsulated. Our exhaustive exploration has
yielded plenty of strategies to amplify the capacity of the pivotal dimension,
ensuring both precision and efficiency. We compare the proposed LightStereo
with existing state-of-the-art methods across various benchmarks, which
demonstrate its superior performance in speed, accuracy, and resource
utilization. LightStereo achieves a competitive EPE metric in the SceneFlow
datasets while demanding a minimum of only 22 GFLOPs, with an inference time of
just 17 ms. Our comprehensive analysis reveals the effect of 2D cost
aggregation for stereo matching, paving the way for real-world applications of
efficient stereo systems. Code will be available at
https://github.com/XiandaGuo/OpenStereo.

LightStereo 是一种创新的立体匹配网络，利用 3D 成本体作为轻量级替代品以加速匹配过程，并通过专注于 3D 成本体的通道维度增强性能，从而在速度、准确度和资源利用方面展现出卓越性能。