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Classification On N Imagenet
评估指标
Accuracy (%)
评测结果
各个模型在此基准测试上的表现结果
| Paper Title | Repository | ||
|---|---|---|---|
| Event Spike Tensor | 48.93 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras | |
| DiST | 48.43 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras | |
| Sorted Time Surface | 47.90 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras | |
| Event Histogram | 47.73 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras | |
| HATS | 47.14 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras | |
| Binary Event Image | 46.36 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras | |
| Timestamp Image | 45.86 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras | |
| Event Image | 45.77 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras | |
| Time Surface | 44.32 | N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras |
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