Get better segmented bird’s-eye view of a scene by using multiple cameras with CoBEVT
Get better segmented bird’s-eye view of a scene by using multiple cameras with CoBEVT
CoBEVT: Cooperative Bird’s Eye View Semantic Segmentation with Sparse Transformers
NOTE: The arXiv site is having problems on July 7, 2022. Hopefully it will be fixed soon.
DeepAI paper abstract https://deepai.org/publication/cobevt-cooperative-bird-s-eye-view-semantic-segmentation-with-sparse-transformers
arXiv paper abstract https://arxiv.org/abs/2207.02202
arXiv PDF paper https://arxiv.org/pdf/2207.02202.pdf
Bird’s eye view (BEV) semantic segmentation plays a crucial role in spatial sensing for autonomous driving.
… recent literature … all based on single-agent camera-based systems which are difficult to handle occlusions and detect distant objects
… Vehicle-to-Vehicle (V2V) communication … enabled autonomous vehicles to share sensing information, which can dramatically improve the perception performance and range as compared to single-agent systems.
… propose CoBEVT, the first generic multi-agent multi-camera perception framework that can cooperatively generate BEV map predictions.
To … fuse camera features from … multi-agent data … design a fused axial attention or FAX module, which can capture sparsely local and global spatial interactions across views and agents.
… CoBEVT achieves state-of-the-art performance for cooperative BEV semantic segmentation.
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