Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report

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dc.contributor.authorIgnatov, Andreyko
dc.contributor.authorMalivenko, Grigoryko
dc.contributor.authorPlowman, Davidko
dc.contributor.authorShukla, Samarthko
dc.contributor.authorTimofte, Raduko
dc.contributor.authorZhang, Ziyuko
dc.contributor.authorWang, Yichengko
dc.contributor.authorHuang, Zilongko
dc.contributor.authorLuo, Guozhongko
dc.contributor.authorYu, Gangko
dc.contributor.authorFu, Binko
dc.contributor.authorWang, Yiranko
dc.contributor.authorLi, Xingyiko
dc.contributor.authorShi, Minko
dc.contributor.authorXian, Keko
dc.contributor.authorCao, Zhiguoko
dc.contributor.authorDu, Jin-Huako
dc.contributor.authorWu, Pei-Linko
dc.contributor.authorGe, Chaoko
dc.contributor.authorYao, Jiaoyangko
dc.contributor.authorTu, Fangwenko
dc.contributor.authorLi, Boko
dc.contributor.authorYoo, Jung Eunko
dc.contributor.authorSeo, Kwanggyoonko
dc.contributor.authorXu, Jialeiko
dc.contributor.authorLi, Zhenyuko
dc.contributor.authorLiu, Xianmingko
dc.contributor.authorJiang, Junjunko
dc.contributor.authorChen, Wei-Chiko
dc.contributor.authorJoya, Shayanko
dc.contributor.authorFan, Huanhuanko
dc.contributor.authorKang, Zhaobingko
dc.contributor.authorLi, Angko
dc.contributor.authorFeng, Tianpengko
dc.contributor.authorLiu, Yangko
dc.contributor.authorSheng, Chuannanko
dc.contributor.authorYin, Jianko
dc.contributor.authorBenavides, Fausto Tko
dc.date.accessioned2023-09-05T12:01:00Z-
dc.date.available2023-09-05T12:01:00Z-
dc.date.created2023-09-05-
dc.date.issued2021-06-
dc.identifier.citation2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)-
dc.identifier.issn2160-7508-
dc.identifier.urihttp://hdl.handle.net/10203/312240-
dc.description.abstractDepth estimation is an important computer vision problem with many practical applications to mobile devices. While many solutions have been proposed for this task, they are usually very computationally expensive and thus are not applicable for on-device inference. To address this problem, we introduce the first Mobile AI challenge, where the target is to develop an end-to-end deep learning-based depth estimation solutions that can demonstrate a nearly real-time performance on smartphones and IoT platforms. For this, the participants were provided with a new large-scale dataset containing RGB-depth image pairs obtained with a dedicated stereo ZED camera producing high-resolution depth maps for objects located at up to 50 meters. The runtime of all models was evaluated on the popular Raspberry Pi 4 platform with a mobile ARM-based Broadcom chipset. The proposed solutions can generate VGA resolution depth maps at up to 10 FPS on the Raspberry Pi 4 while achieving high fidelity results, and are compatible with any Android or Linux-based mobile devices. A detailed description of all models developed in the challenge is provided in this paper.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleFast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report-
dc.typeConference-
dc.identifier.wosid000705890202073-
dc.identifier.scopusid2-s2.0-85116010076-
dc.type.rimsCONF-
dc.citation.publicationname2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationNashville, TN-
dc.identifier.doi10.1109/cvprw53098.2021.00288-
dc.contributor.nonIdAuthorIgnatov, Andrey-
dc.contributor.nonIdAuthorMalivenko, Grigory-
dc.contributor.nonIdAuthorPlowman, David-
dc.contributor.nonIdAuthorShukla, Samarth-
dc.contributor.nonIdAuthorTimofte, Radu-
dc.contributor.nonIdAuthorZhang, Ziyu-
dc.contributor.nonIdAuthorWang, Yicheng-
dc.contributor.nonIdAuthorHuang, Zilong-
dc.contributor.nonIdAuthorLuo, Guozhong-
dc.contributor.nonIdAuthorYu, Gang-
dc.contributor.nonIdAuthorFu, Bin-
dc.contributor.nonIdAuthorWang, Yiran-
dc.contributor.nonIdAuthorLi, Xingyi-
dc.contributor.nonIdAuthorShi, Min-
dc.contributor.nonIdAuthorXian, Ke-
dc.contributor.nonIdAuthorCao, Zhiguo-
dc.contributor.nonIdAuthorDu, Jin-Hua-
dc.contributor.nonIdAuthorWu, Pei-Lin-
dc.contributor.nonIdAuthorGe, Chao-
dc.contributor.nonIdAuthorYao, Jiaoyang-
dc.contributor.nonIdAuthorTu, Fangwen-
dc.contributor.nonIdAuthorLi, Bo-
dc.contributor.nonIdAuthorSeo, Kwanggyoon-
dc.contributor.nonIdAuthorXu, Jialei-
dc.contributor.nonIdAuthorLi, Zhenyu-
dc.contributor.nonIdAuthorLiu, Xianming-
dc.contributor.nonIdAuthorJiang, Junjun-
dc.contributor.nonIdAuthorChen, Wei-Chi-
dc.contributor.nonIdAuthorJoya, Shayan-
dc.contributor.nonIdAuthorFan, Huanhuan-
dc.contributor.nonIdAuthorKang, Zhaobing-
dc.contributor.nonIdAuthorLi, Ang-
dc.contributor.nonIdAuthorFeng, Tianpeng-
dc.contributor.nonIdAuthorLiu, Yang-
dc.contributor.nonIdAuthorSheng, Chuannan-
dc.contributor.nonIdAuthorYin, Jian-
dc.contributor.nonIdAuthorBenavides, Fausto T-
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