SBMVTrack: Spike-Budgeted Multi-View Learning for Energy-Efficient UAV Tracking

Researchers proposed SBMVTrack, a fully spiking neural network framework for energy-efficient UAV visual tracking that introduces Energy-Weighted Spike Budgeting (EWSB) to constrain energy-weighted firing rates and saturation activity, plus Masked Multi-View Target Modeling (MVTM) to improve robustness under the spike budget. Experiments on multiple benchmarks showed SBMVTrack reduces average spike firing rate and theoretical energy consumption while maintaining competitive tracking performance, per the arXiv:2609.25503v1 paper. The source code will be released upon acceptance.

arXiv:2609.25503v1 Announce Type: new Abstract: With sparse and event-driven computation, spiking neural networks show great potential for achieving accurate and energy-efficient UAV visual tracking. However, existing SNN-based trackers typically use spike firing rates only for energy evaluation and lack explicit optimization of actual spike activity. To address this, we propose SBMVTrack, a fully spiking framework for energy-efficient UAV tracking. SBMVTrack introduces Energy-Weighted Spike Budgeting EWSB . EWSB weights actual spike activity according to the computational cost of each spiking layer. It constrains the energy-weighted firing rate and saturation activity, thereby reducing redundant spike computations. To improve tracking performance under the spike budget constraint, we propose Masked Multi-View Target Modeling MVTM . This method treats the initial template, online template, and search region from the same sequence as correlated temporal views. It enhances the robustness of target representations through cross-view feature completion and identity-consistency learning. Extensive experiments on multiple benchmarks demonstrate that SBMVTrack effectively reduces the average spike firing rate and theoretical energy consumption. Meanwhile, it maintains competitive tracking performance, achieving a better accuracy-energy trade-off. The source code will be released upon acceptance.