Attention-Aware Feature Aggregation for Real-Time Stereo Matching on Edge Devices

Jia Ren Chang, Pei Chun Chang, Yong Sheng Chen*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Recent works have demonstrated superior results for depth estimation from a stereo pair of images using convolutional neural networks. However, these methods require large amounts of computational resources and are not suited to real-time applications on edge devices. In this work, we propose a novel method for real-time stereo matching on edge devices, which consists of an efficient backbone for feature extraction, an attention-aware feature aggregation, and a cascaded 3D CNN architecture for multi-scale disparity estimation. The efficient backbone is designed to generate multi-scale feature maps with constrained computational power. The multi-scale feature maps are further adaptively aggregated via the proposed attention-aware feature aggregation module to improve representational capacity of features. Multi-scale cost volumes are constructed using aggregated feature maps and regularized using a cascaded 3D CNN architecture to estimate disparity maps in anytime settings. The network infers a disparity map at low resolution and then progressively refines the disparity maps at higher resolutions by calculating the disparity residuals. Because of the efficient extraction and aggregation of informative features, the proposed method can achieve accurate depth estimation in real-time inference. Experimental results demonstrated that the proposed method processed stereo image pairs with resolution 1242 × 375 at 12–33 fps on an NVIDIA Jetson TX2 module and achieved competitive accuracy in depth estimation. The code is available at https://github.com/JiaRenChang/RealtimeStereo.

原文English
主出版物標題Computer Vision – ACCV 2020 - 15th Asian Conference on Computer Vision, 2020, Revised Selected Papers
編輯Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
發行者Springer Science and Business Media Deutschland GmbH
頁面365-380
頁數16
ISBN(列印)9783030695248
DOIs
出版狀態Published - 2021
事件15th Asian Conference on Computer Vision, ACCV 2020 - Virtual, Online
持續時間: 30 十一月 20204 十二月 2020

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12622 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference15th Asian Conference on Computer Vision, ACCV 2020
城市Virtual, Online
期間30/11/204/12/20

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