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Object segmentation is still considered a challenging problem in autonomous driving, particularly in consideration of real-world conditions. Following this line of research, this paper approaches the problem of object segmentation using LiDAR–camera fusion and semi-supervised learning implemented in a fully convolutional neural network. Our method was tested on real-world data acquired using our custom vehicle iseAuto shuttle. The data include all weather scenarios, featuring night and rainydoi:10.3390/electronics11071119 fatcat:dv4jvexqbfdqjnwiq3qyovdtmy