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Research map / Architectures and efficiency / Spiking networks

EventNet: Asynchronous Recursive Event Processing

CVPR 2019 · Architectures and efficiency › Spiking networks · approach: Event-camera spiking networks · 112 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use EventNet instead of PointNetETHTED+ semantic segmentation · ETHTED+GA [%]: 98.9 -> 99.2Helped
Use EventNet instead of PointNetETHTED+ semantic segmentation · ETHTED+mIoU [%]: 97.4(0.13) -> 97.5(0.22)Helped
Use EventNet instead of PointNetETHTED+ object motion · ETHTED+error [pix/τ]: 3.14(0.08) -> 3.11(0.28)Helped
Use EventNet instead of PointNetMVSEC ego-motion · MVSECerror [deg/sec]: 4.55 -> 4.29Helped
Replace batch PointNet processing with EventNet's recursive event-wise processing and LUTEventNet · 1 MEPS event processingtime per event [μs]: 953.3×10³ -> 1.01Helped
Replace mlp1/2 with a lookup table (ablation)EventNet · 1 MEPS event processingmlp1/2 time per event [μs]: 29.27 -> 0.65Helped
Add temporal decay (ablation)EventNet · ETHTED+ semantic segmentationGA [%]: 99.4 -> 99.2Hurt
Add temporal decay (ablation)EventNet · ETHTED+ object motionerror [pix/τ]: 3.08(0.32) -> 3.11(0.28)Helped
Add temporal rotation (ablation)EventNet · ETHTED+ object motionerror [pix/τ]: 3.74(0.06) -> 3.11(0.28)Helped
Add temporal decay and temporal rotation (ablation)EventNet · ETHTED+ object motionerror [pix/τ]: 4.14(0.32) -> 3.11(0.28)Helped
Add temporal decay (ablation)EventNet · ETHTED+ semantic segmentationmIoU [%]: 98.8(0.16) -> 97.5(0.22)Hurt
Add temporal rotation (ablation)EventNet · ETHTED+ semantic segmentationGA [%]: 98.1 -> 99.2Helped

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