Dynamic token selection and training only 1.6 million parameters instead of over 300 million reduces computation by 48-55% and improves accuracy over prior state-of-the-art on the NuScenes dataset.
BEVFormer V2: Adapting Modern Image Back- bones to Bird’s-Eye-View Recognition Via Perspective Supervision,
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Efficient Multi-View 3D Object Detection by Dynamic Token Selection and Fine-Tuning
Dynamic token selection and training only 1.6 million parameters instead of over 300 million reduces computation by 48-55% and improves accuracy over prior state-of-the-art on the NuScenes dataset.