M2S uses multi-level feature enhancement, auxiliary point cloud reconstruction, and multi-teacher contrastive distillation to boost ego-only 3D mAP by up to 8.64% on V2XSet, V2V4Real, and DAIR-V2X when applied to CoSDH and other detectors.
arXiv preprint arXiv:2308.16714 (2023)
2 Pith papers cite this work. Polarity classification is still indexing.
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Introduces Bayesian fusion for V2X collective perception with hybrid validation, claiming 260% FOV increase and recall rise from 0.82 to 0.94 in roundabout tests.
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C2E: Boosting Ego-Only 3D Object Detection via Multi-Teacher Contrastive Knowledge Distillation
M2S uses multi-level feature enhancement, auxiliary point cloud reconstruction, and multi-teacher contrastive distillation to boost ego-only 3D mAP by up to 8.64% on V2XSet, V2V4Real, and DAIR-V2X when applied to CoSDH and other detectors.