Point-to-Spike Residual Learning for Energy-Efficient 3D Point Cloud Classification
Qiaoyun Wu,
Quanxiao Zhang,
Chunyu Tan
et al.
Abstract:Spiking neural networks (SNNs) have revolutionized neural learning and are making remarkable strides in image analysis and robot control tasks with ultra-low power consumption advantages. Inspired by this success, we investigate the application of spiking neural networks to 3D point cloud processing. We present a point-to-spike residual learning network for point cloud classification, which operates on points with binary spikes rather than floating-point numbers. Specifically, we first design a spatial-aware k… Show more
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