18 citations · 18 across the 5 of their papers we have counts for
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cs.CV2026
A 25-s/inf Event-driven Graph Neural Network Processor with Spatiotemporal Caching and Spline Convolution for Ultra-low-latency AI at the Edge
Adrian Kneip, Martin Lefebvre, Daniel Gehrig +4
Dynamic-vision-sensor (DVS) cameras generate events on a per-pixel basis with a s-level temporal resolution, calling for new algorithm-hardware co-design approaches compared to…
cs.CV2024★ 18 cited
EvGNN: An Event-driven Graph Neural Network Accelerator for Edge Vision
Yufeng Yang, Adrian Kneip, Charlotte Frenkel
Edge vision systems combining sensing and embedded processing promise low-latency, decentralized, and energy-efficient solutions that forgo reliance on the cloud. As opposed to con…