SVL pretraining enables SNNs to reach 85.4% top-1 accuracy on zero-shot 3D classification while outperforming prior SNNs on detection, segmentation, and action recognition with added open-world QA capability.
Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data
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SVL: Spike-based Vision-language Pretraining for Efficient 3D Open-world Understanding
SVL pretraining enables SNNs to reach 85.4% top-1 accuracy on zero-shot 3D classification while outperforming prior SNNs on detection, segmentation, and action recognition with added open-world QA capability.