تقرير
DCVSMNet: Double Cost Volume Stereo Matching Network
العنوان: | DCVSMNet: Double Cost Volume Stereo Matching Network |
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المؤلفون: | Tahmasebi, Mahmoud, Huq, Saif, Meehan, Kevin, McAfee, Marion |
سنة النشر: | 2024 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
الوصف: | 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. |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2402.16473 |
رقم الأكسشن: | edsarx.2402.16473 |
قاعدة البيانات: | arXiv |
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