The content delves into the exploration of visual saliency within continuous spike streams using a spike camera. The introduction of the Recurrent Spiking Transformer (RST) framework enables the extraction of spatio-temporal features from binary spike streams, showcasing superior performance compared to other spike neural network-based methods. The study also includes the creation of a comprehensive real-world spike-based visual saliency dataset enriched with diverse lighting conditions. The experiments demonstrate the effectiveness of the RST framework in capturing and highlighting visual saliency in spike streams, paving the way for new perspectives on SNN-based transformers.
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by Lin Zhu,Xian... a las arxiv.org 03-12-2024
https://arxiv.org/pdf/2403.06233.pdfConsultas más profundas