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arXiv · 2402.16473

DCVSMNet: Double Cost Volume Stereo Matching Network

Mahmoud Tahmasebi·Saif Huq·Kevin Meehan·Marion McAfee
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Abstract

We introduce Double Cost Volume Stereo Matching Network(DCVSMNet) which is a novel architecture characterised by by two small upper (group-wise) and lower (norm correlation) cost volumes. Each cost volume is processed separately, and a coupling module is proposed to fuse the geometry information extracted from the upper and lower cost volumes. DCVSMNet is a fast stereo matching network with a 67 ms inference time and strong generalization ability which can produce competitive results compared to state-of-the-art methods. The results on several bench mark datasets show that DCVSMNet achieves better accuracy than methods such as CGI-Stereo and BGNet at the cost of greater inference time.

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Mahmoud Tahmasebi, Saif Huq, Kevin Meehan, Marion McAfee. 2024-02-26. DCVSMNet: Double Cost Volume Stereo Matching Network. https://doi.org/10.1016/j.neucom.2024.129002

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