Active Spiking Perception: The Membrane Potential as a Belief State for Anytime 3D Point Cloud Recognition
Spiking point cloud networks usually scan space in a fixed, input-agnostic order, which leaves the most distinctive resource of spiking computation, the temporal evolution of the membrane potential, unused as a locus of decision-making. Active Spiking Perception (ASP) recasts 3D recognition as an iterative decision process in which the network's own leaky integrate-and-fire (LIF) membrane potential, read as a running belief over the class, selects the next chunk to observe and triggers confidence-margin early exit. A lightweight Slice-Selection Policy scores unvisited farthest-point-sampled chunks from the membrane state and precomputed geometric descriptors, trains end-to-end through a s...
| Authors | Akarsh Jain, Arya Pawa, Ayush Debnath et al. |
|---|---|
| Primary category | cs.NE |
| Published | 4 August 2026 |
| Last updated at source | 22 August 2026 |
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