Dense Residual Networks for Gaze Mapping on Indian Roads

Dense Residual Networks for Gaze Mapping on Indian Roads

In the recent past, greater accessibility to powerful computational resources has enabled progress in the field of Deep Learning and Computer Vision to grow by leaps and bounds. This in consequence has lent progress to the domain of Autonomous Driving and Navigation Systems. Most of the present rese...

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Veröffentlicht in:arXiv.org 2022-03
Hauptverfasser: Kapoor, Chaitanya, Kumar, Kshitij, Vishnoi, Soumya, Ramanathan, Sriram
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Autonomous navigation
Computer vision
Navigation systems
Roads
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creator Kapoor, Chaitanya
Kumar, Kshitij
Vishnoi, Soumya
Ramanathan, Sriram
description In the recent past, greater accessibility to powerful computational resources has enabled progress in the field of Deep Learning and Computer Vision to grow by leaps and bounds. This in consequence has lent progress to the domain of Autonomous Driving and Navigation Systems. Most of the present research work has been focused on driving scenarios in the European or American roads. Our paper draws special attention to the Indian driving context. To this effect, we propose a novel architecture, DR-Gaze, which is used to map the driver's gaze onto the road. We compare our results with previous works and state-of-the-art results on the DGAZE dataset. Our code will be made publicly available upon acceptance of our paper.
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subjects Autonomous navigation
Computer vision
Navigation systems
Roads
title Dense Residual Networks for Gaze Mapping on Indian Roads
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