Object Recognition on N-Cars
98.4AccuracyMEM
Evaluation results
| Method | Links | |
|---|---|---|
| MEMEvent Repr.=Event count2025.05 | 98.4 | |
| GETEvent Repr.=Event count → Token2025.05 | 96.9 | |
| EVA-L (+ResNet-34)Event Repr.=Learned, Backbone=ResNet-34, Dhead=16, Pre-trained=Gen12025.05 | 96.3 | |
| EventmixTraining Method=STBP, Neural Network=Pre-Act Resnet18, Neuron=PLIF, Timesteps=10, Resolution=(48,48)2024.03 | 96.29 | |
| EventRPG (Saliency Map)Training Method=STBP, Neural Network=Spike-VGG11, Neuron=LIF, Timesteps=10, Resolution=(48,48)2024.03 | 96 | |
| Matrix-LSTMEvent Repr.=Learned2025.05 | 95.8 | |
| EventRPG (CAM)Training Method=STBP, Neural Network=Spike-VGG11, Neuron=LIF, Timesteps=10, Resolution=(48,48)2024.03 | 95.76 | |
| EventDropTraining Method=TET [Deng et al., 2022]2024.03 | 95.46 | |
| IdentityTraining Method=TET [Deng et al., 2022]2024.03 | 94.92 | |
| ESTEvent Repr.=Learned2025.05 | 92.5 | |
| NDATraining Method=STBP-tdBN [Zheng et al., 2021], Neural Network=Spike-VGG11, Neuron=LIF, Timesteps=10, Resolution=(128,128)2024.03 | 91.9 | |
| EVA (+ResNet-14)Event Repr.=Learned, Backbone=ResNet-14, Dhead=16, Pre-trained=N-Cars2025.05 | 91.6 | |
| EVA (+ResNet-14)Event Repr.=Learned, Backbone=ResNet-14, Pre-trained=N-Cars2025.05 | 91.4 | |
| NDATraining Method=STBP-tdBN [Zheng et al., 2021], Neural Network=Spike-VGG11, Neuron=LIF, Timesteps=10, Resolution=(48,48)2024.03 | 90.1 | |
| ALERT-Tr. (+LMM)Event Repr.=Learned2025.05 | 85.6 |