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CLFT: Camera-LiDAR Fusion Transformer for Semantic Segmentation in Autonomous Driving
April 30, 2024, 4:46 a.m. | Junyi Gu, Mauro Bellone, Tom\'a\v{s} Pivo\v{n}ka, Raivo Sell
cs.CV updates on arXiv.org arxiv.org
Abstract: Critical research about camera-and-LiDAR-based semantic object segmentation for autonomous driving significantly benefited from the recent development of deep learning. Specifically, the vision transformer is the novel ground-breaker that successfully brought the multi-head-attention mechanism to computer vision applications. Therefore, we propose a vision-transformer-based network to carry out camera-LiDAR fusion for semantic segmentation applied to autonomous driving. Our proposal uses the novel progressive-assemble strategy of vision transformers on a double-direction network and then integrates the results in …
abstract applications arxiv attention autonomous autonomous driving breaker computer computer vision cs.cv cs.ro deep learning development driving fusion head lidar multi-head network novel object research segmentation semantic transformer type vision vision-transformer
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