The semanticsegmentation of a bird’s-eye view(BEV)is crucial for environment perception in autonomous driving,which includes the static elements of the scene,such as drivable areas,and dynamic elements such as *** p...
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The semanticsegmentation of a bird’s-eye view(BEV)is crucial for environment perception in autonomous driving,which includes the static elements of the scene,such as drivable areas,and dynamic elements such as *** paper proposes an end-to-end deep learning architecture based on 3D convolution to predict the semanticsegmentation of a BEV,as well as voxel semantic segmentation,from monocular *** voxelization of scenes and feature transformation from the perspective space to camera space are the key approaches of this model to boost the prediction *** effectiveness of the proposed method was demonstrated by training and evaluating the model on the NuScenes dataset.A comparison with other state-of-the-art methods showed that the proposed approach outperformed other approaches in the semanticsegmentation of a *** also implements voxel semantic segmentation,which cannot be achieved by the state-of-the-art methods.
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