Dense Residual Networks for Gaze Mapping on Indian Roads
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 29 references that are in the map. First posted on arXiv 22 Mar 2022.
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References · 14
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- 2016Eye Tracking for Everyonecited by 155
- 2015Appearance-Based Gaze Estimation in the Wildcited by 153
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