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Jointly Learning Spatial, Angular, and Temporal Information for Enhanced Lane Detection
May 7, 2024, 4:47 a.m. | Muhammad Zeshan Alam
cs.CV updates on arXiv.org arxiv.org
Abstract: This paper introduces a novel approach for enhanced lane detection by integrating spatial, angular, and temporal information through light field imaging and novel deep learning models. Utilizing lenslet-inspired 2D light field representations and LSTM networks, our method significantly improves lane detection in challenging conditions. We demonstrate the efficacy of this approach with modified CNN architectures, showing superior per- formance over traditional methods. Our findings suggest this integrated data approach could advance lane detection technologies and …
abstract angular arxiv cs.cv deep learning detection imaging information lane detection light lstm networks novel paper spatial temporal through type
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