LightStereo: Channel Boost Is All You Need for Efficient 2D Cost Aggregation

TL;DR

LightStereo introduces a novel, efficient stereo-matching network that leverages channel-boosted 3D cost volumes, achieving high accuracy with minimal computational resources, suitable for real-time applications.

Contribution

The paper proposes a new channel-focused approach to 3D cost volume processing, significantly improving speed and accuracy over traditional 4D cost aggregation methods.

Findings

Achieves competitive EPE on SceneFlow datasets

Runs in 17 ms with only 22 GFLOPs

Ranks 1st on KITTI 2015 among real-time models

Abstract

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 and 17 ms of runtime, and ranks 1st on KITTI 2015 among real-time models. 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.