DRVR uses range-view and geometry-aware voxel-view encoders plus fusion to deliver 5.4% higher mIoU and 2.1x faster inference than multi-sweep baselines on nuScenes-Occupancy from single sweeps.
arXiv preprint arXiv:2308.16896 (2023)
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VQSOP applies sparsity-exploiting vector quantization and a dual-branch refinement module to cut communication volume by up to 82x while claiming state-of-the-art 3D occupancy prediction performance.
citing papers explorer
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Semantic Occupancy Prediction with Dual Range-Voxel Representation
DRVR uses range-view and geometry-aware voxel-view encoders plus fusion to deliver 5.4% higher mIoU and 2.1x faster inference than multi-sweep baselines on nuScenes-Occupancy from single sweeps.
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Sparse-Aware Vector Quantization for Bandwidth-Efficient Collaborative 3D Semantic Occupancy Prediction
VQSOP applies sparsity-exploiting vector quantization and a dual-branch refinement module to cut communication volume by up to 82x while claiming state-of-the-art 3D occupancy prediction performance.