DC Field | Value | Language |
---|---|---|
dc.contributor.author | Paek, Dong-Hee | ko |
dc.contributor.author | Wijaya, Kevin Tirta | ko |
dc.contributor.author | Kong, Seung-Hyun | ko |
dc.date.accessioned | 2022-12-02T09:00:41Z | - |
dc.date.available | 2022-12-02T09:00:41Z | - |
dc.date.created | 2022-12-02 | - |
dc.date.created | 2022-12-02 | - |
dc.date.created | 2022-12-02 | - |
dc.date.issued | 2022-10-08 | - |
dc.identifier.citation | 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022, pp.4328 - 4334 | - |
dc.identifier.issn | 2153-0009 | - |
dc.identifier.uri | http://hdl.handle.net/10203/301502 | - |
dc.description.abstract | Lane detection is one of the most important functions for autonomous driving. In recent years, deep learning-based lane detection networks with RGB camera images have shown promising performance. However, camera-based methods are inherently vulnerable to adverse lighting conditions such as poor or dazzling lighting. Unlike camera, LiDAR sensor is robust to the lighting conditions. In this work, we propose a novel two-stage LiDAR lane detection network with row-wise detection approach. The first-stage network produces lane proposals through a global feature correlator backbone and a row-wise detection head. Meanwhile, the second-stage network refines the feature map of the first-stage network via attention-based mechanism between the local features around the lane proposals, and outputs a set of new lane proposals. Experimental results on the K-Lane dataset show that the proposed network advances the state-of-the-art in terms of F1-score with 30% less GFLOPs. In addition, the second-stage network is found to be especially robust to lane occlusions, thus, demonstrating the robustness of the proposed network for driving in crowded environments. | - |
dc.language | English | - |
dc.publisher | IEEE | - |
dc.title | Row-wise LiDAR Lane Detection Network with Lane Correlation Refinement | - |
dc.type | Conference | - |
dc.identifier.wosid | 000934720604055 | - |
dc.identifier.scopusid | 2-s2.0-85141883332 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 4328 | - |
dc.citation.endingpage | 4334 | - |
dc.citation.publicationname | 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022 | - |
dc.identifier.conferencecountry | CC | - |
dc.identifier.conferencelocation | Macau | - |
dc.identifier.doi | 10.1109/itsc55140.2022.9922341 | - |
dc.contributor.localauthor | Kong, Seung-Hyun | - |
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